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Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
id: string
split: string
lang: string
genre: string
source: string
source_url: string
license: string
tier: string
upstream_dataset: string
upstream_id: string
upstream_url: string
original_sha256: string
original_chars: int64
draft_model: string
response_model: string
judge_model: string
rejected_reason: string
draft: string
rejected: string
chosen: string
to
{'id': Value('string'), 'split': Value('string'), 'lang': Value('string'), 'genre': Value('string'), 'source': Value('string'), 'source_url': Value('string'), 'license': Value('string'), 'tier': Value('string'), 'draft': Value('string'), 'chosen': Value('string'), 'rejected': Value('string'), 'rejected_reason': Value('string'), 'draft_model': Value('string'), 'response_model': Value('string'), 'judge_model': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
split: string
lang: string
genre: string
source: string
source_url: string
license: string
tier: string
upstream_dataset: string
upstream_id: string
upstream_url: string
original_sha256: string
original_chars: int64
draft_model: string
response_model: string
judge_model: string
rejected_reason: string
draft: string
rejected: string
chosen: string
to
{'id': Value('string'), 'split': Value('string'), 'lang': Value('string'), 'genre': Value('string'), 'source': Value('string'), 'source_url': Value('string'), 'license': Value('string'), 'tier': Value('string'), 'draft': Value('string'), 'chosen': Value('string'), 'rejected': Value('string'), 'rejected_reason': Value('string'), 'draft_model': Value('string'), 'response_model': Value('string'), 'judge_model': Value('string')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1879, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | split string | lang string | genre string | source string | source_url string | license string | tier string | draft string | chosen string | rejected string | rejected_reason string | draft_model string | response_model string | judge_model string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dpo_089165dba8bdc4e8 | train | en | social post | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | 1/ spent way too much of this year deep in small-business loan research. here's what actually stuck with me, thread incoming 🧵
2/ biggest myth: banks are the best first stop. reality? they're often the slowest and pickiest. credit unions and online lenders move faster and are way more flexible for smaller amounts.
3... | 1/ spent way too much time this year researching small business loans. these are the main things I actually learned: 🧵 2/ biggest misconception: banks are the way to go. in reality, banks are usually the slowest and most stringent. credit unions and online lenders are much quicker and more flexible for smaller amounts... | 1/ spent the whole year researching small biz loans and holy shit it's confusing as fuck 🤯 here's what I learned... 🧵
2/ if you're starting up, don't even bother with big banks. they want 2+ years financials + perfect credit. try credit unions or local banks instead
3/ SBA loans are intimidating but the 7(a) progra... | Invents facts: 2+ years financials requirement, SBA 7(a), fundbox/bluevine, days-vs-months speed, 'first year'. Drops ca | Claude Sonnet | humanizer 12B SFT checkpoint | GLM-5.3 | |
dpo_a41dd3bf08af6f6e | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | A California rule letting union organizers onto agricultural employers' land for a set period each year amounted to an unconstitutional taking under the Fifth Amendment's Takings Clause. That ruling, Cedar Point Nursery v. Hassid, could signal closer judicial scrutiny of government actions touching property rights gene... | The California law that gave union organizers access to agricultural employers’ land for a certain number of days a year was an unconstitutional taking under the Takings Clause of the Fifth Amendment. In Cedar Point Nursery v. Hassid, the Court may be signaling a greater willingness to scrutinize government actions tha... | The U.S. Supreme Court has issued a decision on the constitutionality of a California law that allows union organizers to enter agricultural employers' land for a fixed time period each year. The Cedar Point Nursery v. Hassid decision may encourage courts to examine the actions of government actors more closely when it... | Cedar Point holding dropped: draft's unconstitutional Fifth Amendment taking ruling reduced to 'decision on constitution | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_49a55b7a541b161d | train | en | student essay | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | # The Case Against Early Sports Specialization
Youth sports have become increasingly competitive, with many parents and coaches pushing children as young as eight or nine to specialize in a single sport year-round. This trend is misguided. Children should be encouraged to play multiple sports throughout their adolesce... | The Case Against Early Sports Specialization
Today's youth sports have become more and more competitive, with parents and coaches pushing their children to play just one sport year-round at young ages—as early as eight or nine years old. This trend is a mistake. Children should be encouraged to participate in multiple... | The Case Against Early Sports Specialization
Over the past several decades, the youth sports landscape has become progressively competitive, with increasing numbers of parents and coaches pushing young athletes as young as eight or nine to specialize in one particular sport year-round. This is a harmful practice, as c... | Invents claim that specialization harms 'mental well being' (draft says physical health and athletic development); also | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_6150cd63b71a4d09 | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | Life insurance contracts combine two distinct features. They offer, first, protection from financial risks whose timing depends on when an insured person dies. They also encompass a wide range of investment arrangements. The hardest questions about taxing life insurance companies stem from these two components. This re... | Life insurance contracts combine two separate characteristics. They provide protection against financial losses that are dependent upon when an insured person dies. They also involve a wide variety of investment arrangements. These two features make the taxation of life insurance companies the source of the most diffic... | Life insurance policies contain two basic elements. They provide insurance against financial risks that depend on the time of death. They also provide a variety of investment options. Issues related to the taxation of life insurance companies arise out of both elements of the product. This report provides a brief summa... | “Went untaxed” was changed to “taxed at a low rate,” altering a central tax fact; “third section” also adds unsupported | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_444567577ac6436e | train | en | incident report | NTSB aviation accident narratives | https://data.ntsb.gov/avdata | Public domain (U.S. federal government work) | A | During the landing roll in the multi-engine airplane, the pilot stated that the aircraft "floated up" into a right bank almost immediately after the wheels made contact, then came back down while still banked to the right. He further noted that he became aware of the damage only after shutting the airplane down in the ... | The pilot reported that the aircraft "floated up" into a right bank as soon as the wheels touched down and then settled back into a right bank as it touched back down. During the landing roll, the pilot stated that the airplane sustained damage to the propeller on the right engine and scarring to the asphalt runway fro... | During the landing roll, the pilot reported that the airplane "floated up" to a right bank almost immediately upon contact with the runway and then descended while in a banked attitude to the right. The pilot also stated that he was not aware of the damage until the airplane had been shutdown in the parking area. Post ... | The rewrite drops that the aircraft was multi-engine and merges the original second and third paragraphs, changing forma | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_049ee011aee9f286 | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | According to the San, they were forced off their ancestral land inside the Central Kalahari Game Reserve (CKGR) unlawfully. International human rights organizations argue that the way the removal was carried out breached international human rights law. Because diamond reserves were later discovered inside the CKGR, adv... | According to the San, they were removed from their ancestral land in the Central Kalahari Game Reserve (CKGR) illegally. International human rights organizations contend that the manner in which the San were removed violated international human rights law. Advocacy groups contend that the discovery of diamond reserves ... | Summary
The San, an indigenous ethnic group of Southern Africa, formerly known as hunter-gatherers, were unlawfully evicted from their ancestral home in the Central Kalahari Game Reserve (CKGR), according to the San. International human rights groups assert that the government's methods in the removal of the San viola... | 1997 relocation wrongly named 'New !Xade' instead of !Xade; drops fact that diamond reserves were later discovered insid | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_fc3fffab05af0e8e | train | zh | opinion essay | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | # 核能:通向低碳未来的必由之路
在全球气候危机日益严峻的今天,核能应当成为我国能源转型的重要支柱。我认为,大力发展核电利大于弊,理由有二。
首先,核能是目前技术最成熟的低碳能源之一。与风能、太阳能相比,核电具有稳定性强、不受天气影响的优势,能够提供持续可靠的基荷电力。一座百万千瓦级核电站每年可减少数百万吨二氧化碳排放,相当于种植数千万棵树木。在"双碳"目标的压力下,若仅依赖间歇性的可再生能源,电网调峰将面临巨大挑战,而核能恰好能弥补这一短板,成为清洁能源体系中不可或缺的一环。
其次,核能的能量密度远超传统化石燃料,土地利用效率极高。一座核电站占地面积远小于同等发电量的光伏电站或风电场,这对于人多地少的国家而言意义重大。此外,... | 核能是通向低碳未来的必由之路!
随着全球气候危机的加剧,核能应该成为我国未来能源转型的重要组成部分。我认为大力发展核电是利大于弊的,主要有以下两点原因:
首先,核能是目前最成熟的低碳能源之一。相比于风能、太阳能,核电具有稳定性和不受天气条件限制的特点,可以提供持续稳定的基荷电力。一个百万千瓦级的核电站每年可以减排数百万吨的二氧化碳,相当于植树造林数千万棵。在"双碳"目标下,如果仅靠间歇性的可再生能源,电网的调峰会面临巨大挑战,而核能可以很好地弥补这一不足,成为清洁能源体系的重要组成部分。
其次,核能的能量密度远远高于传统化石燃料,且土地利用效率非常高。核电站的占地面积远低于同等发电量的光伏电站或风电场,这对于人口众多、土地稀缺... | 在当前“双碳”目标的驱动下,核电作为清洁、高效、稳定的能源,应该成为中国能源结构的重要组成部分。我认为,发展核电对中国有诸多好处,具体理由如下:
首先,核电是实现低碳减排的重要手段。与风能、太阳能等其他新能源相比,核电具有高能量密度、稳定可靠的发电特性,能实现全天候、大规模的电力供应,有效克服新能源发电的间歇性难题。在“双碳”目标的背景下,为了满足经济发展的电力需求并大幅度降低碳排放,核电几乎是唯一的选择。法国的核电占能源消费的80%以上,碳排放强度远低于大多数欧洲国家。
其次,核电具有高经济效益和高技术自主性。核电站的建设投资虽高,但运营成本低,发电效率高,具有显著的经济效益。发展核电有助于我国在核燃料循环、反应堆设计等领域的... | Invents facts (France 80% nuclear, 华龙一号 exports, cost/efficiency claims); drops deaths-per-unit statistic, CO2 reduction | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_fae825d1b633cfe1 | train | en | peer review | PeerRead (ACL 2017 / CoNLL 2016 reviews) | https://github.com/allenai/PeerRead | CC BY 4.0 | A | I assume that what you call "elementary APTs" are a triple consisting of a target word w, a dependency path r, and another word w'. The terminology strikes me as somewhat confusing.
Could you clarify whether "shifted PMI" refers to the PMI defined in equation (3)?
"Removing features which tend to go with lots of thin... | I assume you mean by "elementary APTs" a triple made of a target word w, a dependency path r and a word w'. The term sounds a bit confusing to me.
Could you explain what you mean by "shifted PMI"? Is it the PMI defined in equation (3)?
"Removing features which tend to go with lots of things (low positive PMI) means t... | I guess you mean that your "elementary APTs" are defined as a triple of (a target word w, a dependency path r and another word w'). I find the terminology somewhat confusing.
Do you mean the PMI as defined in (3)?
"Removing features which tend to go with lots of things (low positive PMI) means that these phrases appea... | The request to clarify whether “shifted PMI” refers to the PMI in equation (3) loses the term “shifted,” changing the sp | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_ba46614692e1832d | train | en | paper abstract | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | # Introduction
The steady contraction of local journalism over the past two decades has raised significant concerns among scholars, policymakers, and civic organizations about the health of democratic institutions at the community level. Since the early 2000s, the United States and other democracies have witnessed a m... | Introduction
The ongoing decline of local news outlets over the last two decades has prompted concern among scholars, policymakers, and advocacy groups regarding the state of democratic governance at the local level. The U.S. and other democratic nations have experienced a dramatic loss in the number of local news out... | Introduction
The American local news landscape has undergone a significant transformation over the past two decades. Thousands of newspapers have closed, media consolidation has intensified, and traditional advertising models have collapsed, leading to the emergence of what scholars have dubbed "news deserts," areas wi... | Invents claims (political polarization, quality-vs-presence gap) and a new methodology (original survey data, content an | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_f2e7f6619b8535da | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | State law sets up several funding mechanisms, each with a specified starting capitalization level and restrictions on how the money can be used. Local governments have the option of entering interjurisdictional agreements to provide emergency services together. The DEM is authorized to stand up an emergency volunteer r... | There are several methods for funding emergency operations that are established in state law with a predetermined amount of capitalization and certain limitations on use. Local governments may enter into interjurisdictional agreements for the provision of emergency services. The DEM may establish an emergency volunteer... | Certain laws establish funding mechanisms with a specific capitalization amount and conditions for its use. Local jurisdictions may make interjurisdictional agreements to provide emergency services. The DEM is authorized to establish an emergency volunteer reserve cadre. The Arkansas Emergency Interim Legislative Succe... | Invented claim 'These profiles are descriptive only; they are not analytical' not in DRAFT; drops 'Readers in Congress' | Claude Sonnet | humanizer 12B SFT checkpoint | GLM-5.3 |
dpo_61506ef087986e53 | train | en | reddit post | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | Title: Torn between full vegan and staying vegetarian — need a reality check
I’ve been vegetarian for about six years, mostly for animal welfare reasons, but lately I’ve been seriously considering going fully vegan. The thing holding me back is my living situation: I share a kitchen with two roommates who eat dairy an... | Title: Torn between full vegan and staying vegetarian - need a reality check
I've been vegetarian for about 6 years, mostly for animal welfare, but recently I've been considering making the switch to full vegan. The issue I have is I share a kitchen with 2 roommates who constantly eat dairy and eggs, we share a gro... | I've been vegetarian for a few years, mostly due to animal welfare issues, but lately I've been feeling really compelled to make the jump to veganism. My main issue is that I live with 2 other people that are constantly eating dairy and eggs, and we share a kitchen and groceries, so it's hard to avoid cross-contaminati... | 'About six years' vegetarian became 'a few years' — a dropped duration/fact; also 'smaller cities' and addressing those | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_698148945518345f | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | Discussion has turned to naming someone described variously as an "independent counsel," a "special prosecutor," or a "special counsel" to run the criminal inquiry into what has come to be called the "Enron matter." Federal law at present contains no mechanism for appointing an "independent counsel," since that statuto... | Discussion has focused on the appointment of a person to be called an “independent counsel,” a “special prosecutor,” or a “special counsel” to investigate the criminal aspects of the “Enron matter.” At this time, there is no statutory authority for the Attorney General to appoint an “independent counsel,” as this provi... | Currently, however, there is no law in place providing for the appointment of an “independent counsel” – that statutory provision expired and was not renewed by Congress after June 30, 1999. Thus, no “independent” counsel or special prosecutor can be appointed by a neutral three-judge panel at the request of the Attorn... | The opening fact that discussion concerns naming an Enron-investigation counsel is omitted; the draft’s trailing partial | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_fa9c931ac94027ff | train | en | peer review | eLife peer reviews and decision letters | https://github.com/elifesciences/elife-article-xml | CC BY 4.0 (eLife) | A | In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.
**Acceptance summary:**
This manuscript by Dubey and colleagues substantially builds on the interesting findings they reported in an eLife paper in 2018. Using a creative strategy, they demo... | In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.
Acceptance summary:
The work by Dubey and colleagues represents a significant extension of interesting findings from their eLife paper in 2018.
Using a clever approach, they show that R-spo... | In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The manuscript by Dubey et al.
significantly expands on the interesting results they published in an eLife paper in 2018.
They present creative strategy to show that R-spon... | none | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_924bf3d982388876 | train | en | paper section | PeerRead (ACL 2017 / CoNLL 2016 reviews) | https://github.com/allenai/PeerRead | CC BY 4.0 | A | This paper proposes turning relation extraction into a question-answering task. The core idea is that questions can carry content more generically than specific relation examples do, and are simpler to construct. The reported results look strong, although the paper never runs a direct comparison against a standard rela... | The paper presents the idea of using question answering as a way to solve relation extraction. The idea is that questions are more generic than specific examples of relations and easier to generate. The results appear to be quite good, but no direct comparison with a standard relation extraction dataset is provided.
-... | The paper presents an idea of framing relation extraction as a question answering task. It is motivated by the idea that questions are more generic and easier to generate than specific examples of relations. It also claims good results, but it never performs a direct comparison with a standard relation extraction datas... | Strengths clause confuses 'questions it hasn't seen' with 'relations it hasn't seen,' making the unseen/seen distinction | Claude Sonnet | humanizer 12B SFT checkpoint | GLM-5.3 |
dpo_5a2dabde0e2cd007 | train | en | social post | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | 1/ Spent this year deep in e-bike world and honestly it changed how I think about getting around. Quick thread on what I learned 🚲⚡️
2/ Torque sensors > cadence sensors. Torque-based pedal assist actually feels like you're riding a bike, not being launched by a rocket every time you tap the pedal. Worth the extra $$$... | 1/ So I’ve been living the e-bike life this year and it’s transformed how I approach transportation. Let’s talk e-bike stuff 🚲⚡️
2/ Torque sensors are king over cadence sensors. Torque-sensing pedal assist means you’re pedaling, not rocket-launching with every pedal stroke. It’s worth the extra $$$.
3/ E-bike batter... | 1/ Lived in the e-bike world this year and it’s a game changer. Here’s a quick thread on what I’ve learned about e-bikes 🚲⚡️ 2/ Torque > cadence sensors. Torque-based pedal assist makes you feel like you’re actually riding a bike, not getting shot out of a cannon when you touch the pedal. Worth the extra $$$. 3/ Batte... | 'basically fiction' hardened to 'literally made up'; 'changed how I think about getting around' softened to generic 'gam | Claude Sonnet | humanizer 12B SFT checkpoint | GLM-5.3 | |
dpo_6253f2e96ec37ace | train | en | peer review | eLife peer reviews and decision letters | https://github.com/elifesciences/elife-article-xml | CC BY 4.0 (eLife) | A | As part of its commitment to openness, eLife makes available the most significant revision requests together with the authors' responses.
Acceptance summary:
The authors show that CCK+ interneurons form functional subpopulations distinguishable by how they fire. They uncover the mechanism responsible for this heterog... | In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The authors demonstrate functional heterogeneity of CCK+ interneurons, which is related to their distinct firing patterns.
They identify the mechanism underlying this hetero... | In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The authors reveal that CCK+ interneurons are heterogeneous by firing patterns.
They unravel the mechanism underlying this diversity and demonstrate that the firing pattern ... | Adds the claim that the reviewers discussed the reviews together and explicitly took one another's views into account; p | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_1ccce49a9671b3e1 | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | The texts of most of these amendments either mirror the proposed federal amendment or restate the Equal Protection Clause of the Fourteenth Amendment to the U.S. Constitution. When these amendments were enacted, and how they were worded, reflect both the rise and decline of the women's movement in the United States and... | In most cases the wording of these amendments either mirrors the text of the proposed federal amendment, or else echoes the language of the Equal Protection Clause of the 14th Amendment to the U.S. Constitution. The adoption of these amendments and the wording chosen to accomplish it, reflect the ascendance and retreat... | Most of the texts of these amendments are either identical to the proposed federal amendment or restate the Equal Protection Clause of the Fourteenth Amendment to the U.S. Constitution. The time when and the form in which these amendments have been enacted reflects both the emergence and demise of the women’s movement ... | The explicit 1978–1997 period with no state ERAs is omitted, and “approved” is changed to “ratified”; History is also sp | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_b3895dbff8ee9bf8 | train | en | paper abstract | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | # Introduction
Wildfire risk has escalated dramatically across fire-prone regions over the past two decades, driven by a combination of climatic change, prolonged drought conditions, and expanding residential development in the wildland-urban interface (Author et al., 2019). These trends have placed unprecedented pres... | Introduction
Over the past two decades, the risk of wildfires has dramatically increased in many fire-prone regions, due in large part to climate change, prolonged periods of drought, and increased residential development in the wildland-urban interface (Author et al., 2019). These trends have put significant pressure ... | Introduction
Wildfires have become one of the most disruptive natural hazards of the 21st century, with tens of billions of dollars in annual economic losses in fire-prone areas (Author et al., 2019). As fire seasons lengthen and burn severity increases in the context of climate change, insurers are facing new and grow... | Invents facts (tens of billions in losses, rate caps, household survey data, new citations like Author & Author 2017/202 | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_0e1e08ec403aa60e | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | State law sets up several funding mechanisms, each with a specified starting capitalization level and restrictions on how the money can be used. Local governments have the option of entering interjurisdictional agreements to provide emergency services together. The DEM is authorized to stand up an emergency volunteer r... | State law establishes several funding mechanisms with specified initial levels of capitalization and uses. Local governments can enter into interjurisdictional agreements for the provision of emergency services. The DEM is empowered to establish an emergency volunteer reserve cadre. The Arkansas Emergency Interim Legis... | State law provides several funding mechanisms, with specific initial capitalization and spending limitations. Local governments may enter interjurisdictional agreements for joint provision of emergency services. The DEM is given authority to establish an emergency volunteer reserve cadre. The Arkansas Emergency Interim... | none | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_e7d76ebaad0de223 | train | en | paper abstract | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | Discussion
The present study examined the impact of AI-based instructional tools on student learning outcomes and found a modest, statistically significant effect. This suggests that AI integration can meaningfully, though not dramatically, enhance classroom learning compared to traditional instruction alone. The magn... | Discussion
This study investigated the effect of AI-based instruction tools on student learning outcomes, demonstrating a modest and statistically significant effect. These findings suggest that AI integration can have a meaningful but not dramatic effect on learning in classrooms, as opposed to traditional instruction... | Discussion
The results of this study provide evidence of a modest, but statistically significant positive impact of AI-assisted instruction on student learning outcomes. While the effect size suggests that AI tools are not likely to be a silver bullet, the positive impact of AI tools on student learning outcomes in th... | Dropped facts: novelty/adaptation explanation, prior technology exposure moderator, socioeconomic/cultural limitation de | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_5601ff01bb64cae4 | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | President Ricardo Lagos took office in March 2000 for a six-year term, heading the third government elected in Chile since civilian rule was restored. The country has managed its democratic transition well, though relations between civilians and the military have periodically been strained. When former military ruler G... | President Ricardo Lagos, sworn in March 2000 for a six-year term, is the head of the third democratically elected government in Chile since the return to civilian rule. Chile's democratic transition has been smooth, although tensions have surfaced occasionally in the civil-military relationship. Arrests of former milit... | President Ricardo Lagos, sworn into office in March 2000, is the head of the third government chosen under Chile's democratic system since the restoration of civilian rule. Chile has successfully navigated the process of political transition, although civilian-military relations have periodically been tense. The arrest... | DRAFT states Lagos took office 'for a six-year term'; OUTPUT drops the term length entirely. | Claude Opus | humanizer 12B SFT checkpoint | GLM-5.3 |
dpo_1a31a7f768a2b85e | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | Summary
Private immigration bills call for particular attention to precedent, since they represent a special form of relief that allows named individuals to bypass the general immigration and nationality laws in cases found to be uniquely deserving. This report surveys the procedure and precedents that congressional su... | Summary
Private immigration bills require special attention to precedent, because they are a special type of relief that enables specific persons to circumvent the general immigration and nationality laws where cases are deemed to be particularly deserving. This report reviews the procedure and precedents followed by c... | Summary
Private immigration bills warrant special attention to precedent because they represent a specific kind of immigration relief that enables named individuals to avoid the general immigration and nationality laws when their individual cases are deemed uniquely deserving. This report reviews the procedure and prec... | none | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_19bdb1e1d3248496 | train | en | paper abstract | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | ## Discussion
The present study found that the adaptation intervention produced a modest but statistically significant improvement in household resilience outcomes relative to comparison sites. While the magnitude of the effect was smaller than anticipated based on prior pilot work, the consistency of the direction of... | Discussion
The findings of the present study suggest that the adaptation intervention provided a marginal, but statistically significant, improvement in household resilience outcomes, compared to comparison sites. While the effects observed were less pronounced than what we expected based on previous pilot studies, the... | Discussion
Our results show that the adaptation intervention had a modest but statistically significant impact on the outcome variables of interest. Although this effect size was smaller than expected, the fact that the effect was consistent across subgroups confirms that the adaptation intervention did contribute to i... | Invents new research recommendations (qualitative methods, climate shocks/seasonal cycles) and drops facts: pilot-work c | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_5ae15a8232b4a996 | train | zh | social post | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | 说实话,我对公共交通的感情挺复杂的,又爱又恨。
先说爱的部分。我之前在国内的时候,每天挤地铁上下班,虽然高峰期人挤人挤得跟沙丁鱼罐头似的,但你不得不承认,那种效率是真的高。北京上海这种大城市,地铁网络密到你随便一个地方,走个十分钟总能找到站,而且准点率高到离谱,基本不用担心迟到这种事。我记得有一次赶飞机,打车怕堵车,最后果断选了地铁,结果准时到达,司机朋友还堵在半路上呢。那一刻真的觉得,公共交通不只是省钱,关键时刻是真的靠谱。
后来我在国外待过一段时间,才真正体会到落差感。有些城市的公交系统,班次少得可怜,晚上八九点之后基本就没车了,你要是加班晚了,只能打车,一趟车费顶你好几天的公交费。而且很多地方设计得也不人性化,换乘要走特别... | 说实话,我对于公共交通的情感既爱又恨。
先来说爱,我在国内的时候,每天挤地铁上下班,虽然高峰时期挤得像沙丁鱼罐头一样,但不得不说,效率是真的高。在比如像北京上海这样的大城市,地铁网密得你随便一个地方,走10分钟都能找到地铁站,而且准点率高到离谱,你基本不需要担心迟到。我记得有一次赶飞机,打车怕堵车,最后果断选择了地铁,结果准时到达,司机朋友还堵在半路上。那一刻我觉得,公共交通不仅能省钱,关键时候是真的靠谱。
后来我去了国外待了一段时间,才体会到落差感。有些城市的公交系统,班次少得可怜,晚上八九点之后基本就没车了,你要是加班晚了,只能打车,一趟车费顶你好几天的公交费。而且很多地方设计得也不人性化,换乘要走特别远,或者压根没有直达的... | 爱恨交织。
爱:在国的时候,每天坐地铁上班,高峰期人挤人像沙丁鱼罐头,但是不得不承认,这效率真的高,北京上海这种大城市,地铁网密如麻,你在哪都能找到地铁站,10分钟总能走到,准点率也是绝了,我记得有次赶飞机,打车怕堵车,直接选了地铁,结果准时到达,打车司机朋友堵在半路上…公共交通不仅仅是省钱,在关键时候真的靠谱。
恨:之后去过一段时间国外,才真正体会到什么叫落差,有些城市,公交车班次少到哭,晚上八九点基本就没有了,你要是加班晚了,只能打车,一天车费顶你好几个月公交费,很多设计也不人性化,换乘走老远,或者压根没有直达的,逼着你买车。这才意识到,原来好的公共交通并不是理所当然的,它其实是城市管理水平和投入的直接体现。
所以现在看待... | Changed '一趟车费顶你好几天的公交费' to '一天车费顶你好几个月公交费' (天→月, amount reversed); also '在国内' garbled to '在国的时候'. | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 | |
dpo_d095b2b2675ae80e | train | en | project report | Apache Software Foundation board minutes | https://www.apache.org/foundation/records/minutes/ | Apache-2.0 (The Apache Software Foundation) | A | Aries completed its Incubator graduation on 15th December 2010. Most, though not all, of the items on the list of transfers from the Incubator to TLP have been finished.
Work on the 0.3 release is under way, currently focused on eliminating snapshot dependencies by cooperating with the projects Aries relies on so that... | On 15th December 2010 Aries has successfully graduated from the Incubator. Most (but not all) of the items on the list of transfers from Incubator to TLP are completed. Development of the 0.3 release is underway and the main work is removing snapshot dependencies through collaboration with the projects that Aries depen... | Aries successfully graduated from Incubator on 15th December 2010. Most, if not all, the transfer items from Incubator to TLP are being completed.
Development for the 0.3 release is underway, with the primary focus being on removing the snapshot dependencies by coordinating with the projects that Aries depends upon to... | “Have been finished” changes to “are being completed,” altering the transfer items’ status from completed to ongoing. | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_3bfe9080c9760294 | train | en | paper section | PeerRead (ACL 2017 / CoNLL 2016 reviews) | https://github.com/allenai/PeerRead | CC BY 4.0 | A | Strengths:
- The paper tackles a question that matters a lot for NMT: what the model actually picks up about morphology, syntax, and related properties.
- The goals are stated clearly and the experiments follow through on them well. The review of prior work and the comparisons against it are solid, and overall the pap... | Strengths:
- The paper addresses an important question for NMT - what does the model learn about morphology, syntax, etc.
- The paper's goals are well-defined and the experiments effectively address them. The review of previous work and comparison is good and the paper is enjoyable to read.
- The approach in the experi... | Strengths:
- The paper addresses a key question for NMT, what does the model learn about morphology, syntax, etc.
- The paper's objectives are clearly articulated and the experiments are well-justified. The literature review and comparison is good.
- The experiments are well set up; the paper trains POS and morphologi... | DRAFT's 'if three was already too many' becomes 'if there were too many', dropping the number three; also the opinion 't | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_ca5d4990dd614f52 | train | en | policy report | Congressional Research Service reports | https://www.everycrsreport.com/ | Public domain (U.S. federal government work) | A | The United States Flag: Federal Law Relating to Display and Associated Questions
Background
Because the public worries about, and is confused by, what counts as proper respect for the United States flag, questions have multiplied about the law covering how the flag is handled, displayed, and used. Legislation on the ... | The United States Flag: Federal Law Regarding Display and Related Issues
Background
The issue of how to properly honor the United States flag has concerned and confused the public and raised questions concerning the law governing the display, treatment, and use of the flag. Both the states and the federal government ... | The United States Flag: Federal Law Relating to Display and Associated Questions
Background
Public concern and confusion about what constitutes proper respect for the United States flag has generated numerous questions about the law governing the handling, display, and use of the flag. The issue has been addressed in... | Draft says Congress separately designated the national anthem; output attributes this to 'The Code' itself, changing who | Claude Opus | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
dpo_b7768124bc9ebee3 | train | en | incident report | NTSB aviation accident narratives | https://data.ntsb.gov/avdata | Public domain (U.S. federal government work) | A | The left wing had separated at roughly half its span. Its inner half, together with part of the left wing flap, remained attached to the fuselage. The outer half was located on a heading of 100 degrees, approximately 43 feet from the fuselage. The wingtip tank and a section of the aileron were still connected to it. Se... | The left wing had broken away at about mid span. The inboard half and part of the left wing flap remained attached to the fuselage. The outboard half of the left wing was found on a heading of 100 degrees, about 43 feet away from the fuselage. The wingtip tank and part of the aileron remained attached. Parts of the ail... | The left wing had broken in half, with its inside portion and portion of the left wing flap attached to the fuselage. The outer wing portion was on a heading of approximately 100 degrees, approximately 43 feet aft of the fuselage. The wing tip tank and a portion of the aileron remained attached. Portions of the aileron... | The draft says the outer wing was approximately 43 feet from the fuselage; the rewrite says 43 feet aft, changing its lo | GLM-5.3 | humanizer 4B SFT checkpoint | GPT-5.6 Luna |
dpo_227b87885fe368c8 | train | en | paper abstract | AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A (AI-written) | # Introduction
The rapid and widespread adoption of remote work arrangements has fundamentally transformed the landscape of contemporary employment. What began as a niche practice confined largely to freelancers and select technology firms has, over the past several years, become a mainstream mode of organizing labor ... | Introduction
The widespread adoption of remote working arrangements has profoundly reshaped the landscape of modern employment. Once a niche practice primarily used by freelancers and certain technology companies, remote work has in recent years evolved into a mainstream approach to organizing work across industries a... | Introduction
The COVID-19 pandemic brought about a drastic and unplanned shift to remote work, turning it from a niche employment option into a mainstream work arrangement (Author et al., 2020). Before 2020, remote work was usually adopted selectively by knowledge-intensive firms and provided as a flexible benefit, rat... | Invents COVID-19 pandemic as cause; changes research question from sustained remote work/productivity/well-being with mo | Claude Sonnet | humanizer 4B SFT/DPO checkpoints | GLM-5.3 |
humanizer-data
Training data for humanizer v2, a 12B model that rewrites AI-written drafts (English and Chinese) so they read like a person wrote them, keeping every fact. Code and app: GitHub. How the data was built, step by step: docs/DATA.md (中文).
Only rows that were actually used to train v2 are here, one config per training step:
| Config | Training step | Used in training | With text | Reference only | Removed before release |
|---|---|---|---|---|---|
rewrite_sft |
SFT: AI draft → human original | 28,560 | 5,471 | 21,632 | 1,457 |
dpo |
DPO: draft, chosen rewrite, rejected rewrite | 4,124 | 1,068 | 2,619 | 437 |
rl_prompts |
RL, three rounds: drafts only (the reward came from an LLM judge, no reference answer) | 5,299 | 1,264 | 3,744 | 291 |
eval_drafts |
Not trained on: the evaluation drafts from the model card, written from scratch by models | — | 311 | — | — |
Splits are licenses
| Split | What | Rows (SFT / DPO / RL) |
|---|---|---|
redistributable |
Public-domain or openly licensed human text (U.S. government reports, CC BY, ODC-BY, Apache-2.0), plus drafts an AI wrote from a scenario with no human original. Full text. | 4,932 / 821 / 965 |
noncommercial |
CC BY-NC-SA human text (PERSUADE 2.0, wikiHow, OpenStax). Full text; non-commercial, share-alike. | 539 / 247 / 299 |
reference_only |
Sources whose license does not let us pass the text on. No text: source dataset, record ID/URL where we could recover it, SHA-256 and length of the exact text we trained on. The draft is withheld too (it is a close rewrite of the original). Rebuild with scripts/rebuild_reference_only.py. |
21,632 / 2,619 / 3,744 |
Every row has a license and tier column; follow the license of each row. In rewrite_sft and dpo, split = train or validation (validation rows only measured loss to pick the checkpoint).
from datasets import load_dataset
sft = load_dataset("jialinyyzz/humanizer-data", "rewrite_sft", split="redistributable")
print(sft[0]["draft"][:300], "\n---\n", sft[0]["original"][:300])
Sources
| Source | License | Tier | Rows published (SFT / DPO / RL) |
|---|---|---|---|
| Congressional Research Service reports | Public domain (U.S. federal government work) | A · redistributable | 3,490 / 216 / 58 |
| eLife peer reviews and decision letters | CC BY 4.0 (eLife) | A · redistributable | 1,268 / 52 / 12 |
| NTSB aviation accident narratives | Public domain (U.S. federal government work) | A · redistributable | – / 95 / 147 |
| Apache Software Foundation board minutes | Apache-2.0 (The Apache Software Foundation) | A · redistributable | – / 99 / 142 |
| Project Gutenberg | Public domain in the U.S. (Project Gutenberg, headers removed) | A · redistributable | – / – / 194 |
| PeerRead (ACL 2017 / CoNLL 2016 reviews) | CC BY 4.0 | A · redistributable | 94 / 32 / – |
| peS2o (s2orc open-access subset) | ODC-BY 1.0 | A · redistributable | 80 / 2 / 7 |
| NIH RePORTER project abstracts | ODbL 1.0 (NIH RePORTER on data.gov) | A · redistributable | – / – / 46 |
| NSF award abstracts | Public domain (U.S. federal government work); NSF award abstracts | A · redistributable | – / – / 19 |
| AI-written from a scenario prompt (no human original) | AI-generated draft; see model terms | A · AI-written | – / 325 / 340 |
| PERSUADE 2.0 | CC BY-NC-SA 4.0 | B · non-commercial | 539 / 219 / 232 |
| wikiHow | CC BY-NC-SA 3.0 (wikiHow) | B · non-commercial | – / 28 / 66 |
| OpenStax textbooks | CC BY-NC-SA 4.0 (OpenStax) | B · non-commercial | – / – / 1 |
| PubMed abstracts (via MedRAG/pubmed) | Publisher/author copyright (NLM does not grant rights) | C · reference only | 4,933 / 327 / 115 |
| python-dev mailing list archive | No license (each sender holds copyright) | C · reference only | 4,289 / 507 / 28 |
| Zhihu-KOL (Zhihu answers) | No license (Zhihu user content) | C · reference only | 2,161 / 182 / 143 |
| COIG-CQIA | No license stated (mixed platform content) | C · reference only | 1,953 / 160 / 126 |
| Blog Authorship Corpus | Non-commercial research use; redistribution not granted | C · reference only | 1,791 / 135 / 254 |
| AESLC / Enron email | No license stated | C · reference only | 1,641 / 336 / 83 |
| Enron email corpus (CMU) | No license stated | C · reference only | 1,657 / 231 / 82 |
| Hacker News comments | Hacker News terms (no redistribution) | C · reference only | 1,260 / 159 / 5 |
| Webis-TLDR-17 (Reddit) | CC BY 4.0 from the aggregator over Reddit user content (not cleared with authors) | C · reference only | 923 / 67 / 173 |
| CSL (Chinese scientific abstracts) | Journal/author copyright | C · reference only | 491 / 53 / 315 |
| Webis-CMV-20 (Reddit r/changemyview) | CC BY 4.0 from the aggregator over Reddit user content (not cleared with authors) | C · reference only | – / 38 / 439 |
| IMDb Large Movie Review Dataset | No license stated (IMDb user content) | C · reference only | 286 / 24 / – |
| Listed-company announcements (Duxiaoman-DI/FinCorpus) | Aggregator license; content not cleared | C · reference only | – / – / 308 |
| Stack Exchange data dump (2021) | CC BY-SA, but author attribution not kept in our copy | C · reference only | – / 90 / 207 |
| Amazon Reviews 2023 (McAuley Lab) | No license stated (user content) | C · reference only | – / 57 / 222 |
| Paul Graham essays | All rights reserved | C · reference only | 246 / 20 / – |
| NASA ASRS report narratives | No written license for reporter narratives | C · reference only | – / 101 / 156 |
| ASAP-AES (Kaggle) | Kaggle competition data (no redistribution) | C · reference only | – / 70 / 161 |
| MNBVC (Tianya forum) | Aggregator license; content not cleared | C · reference only | – / 3 / 227 |
| Tweets (enryu43/twitter100m_tweets) | X/Twitter terms (post IDs only) | C · reference only | – / – / 156 |
| LinkedIn posts (Kaggle) | Platform terms (no redistribution) | C · reference only | – / – / 139 |
| People's Daily commentaries (Papersnake/people_daily_news) | People's Daily copyright | C · reference only | – / 2 / 117 |
| THUCNews (Sina News) | Sina News copyright; commercial use needs a license | C · reference only | – / 8 / 94 |
| Dianping reviews (yf_dianping) | No license (user content) | C · reference only | – / 1 / 75 |
| Yelp reviews (Yelp/yelp_review_full) | Yelp dataset agreement (no redistribution) | C · reference only | – / – / 76 |
| CNN/DailyMail | Article copyright retained by CNN / Daily Mail | C · reference only | – / 47 / 4 |
| nlp_chinese_corpus (brightmart) | Aggregator license; content not cleared | C · reference only | – / – / 14 |
| NUS Corpus of Learner English | NUS license (non-sublicensable) | C · reference only | – / – / 13 |
| WritingPrompts (Reddit) | Aggregator license over Reddit user content | C · reference only | – / – / 10 |
| Mixed academic text | Mixed source; not redistributed | C · reference only | 1 / 1 / 2 |
AI-written side: check the model terms
Drafts were written by GLM-5.3, GPT-5.6 Luna, Claude Opus, Claude Sonnet and Muse Spark (draft_model column); the DPO rewrites came from earlier checkpoints of humanizer and were judged by GLM-5.3 or GPT-5.6 Luna. These providers restrict using outputs to train other models (Anthropic and OpenAI: no competing models; Zhipu's mainland-China platform: no training of other models at all). Links in DATA.md. You are responsible for complying with them.
Privacy
All text fields were scanned before release. Rows mentioning the project author were removed everywhere; rows with any email address, phone number or ID number were removed from the two splits that carry text. Some openly licensed sources (U.S. government reports, Apache board minutes) name public officials and contributors, as in the originals.
Dates
v2 was trained on 178 rows (SFT / DPO / RL: 167 / 8 / 3) whose Zhihu answer is dated after 2022-11-30 (for the Zhihu subset of COIG-CQIA the date is inferred from the answer ID), 1,426 rows (1,148 / 169 / 109) whose peS2o paper is dated after 2022-11-30 (1,396 of them in December 2022), and 11 rows from CRS reports whose latest version is dated after 2022-11-30. All of these are left out of this release. 1,879 human texts have no date we could check, mostly the non-Zhihu parts of COIG-CQIA (1,817); they are kept.
Limitations
- Most human text is reference-only; rebuilding it depends on upstream sources staying online, and our texts are often tidied excerpts, so a rebuild may differ slightly.
- The judges are LLMs: strict, sometimes flagging harmless rewording, and they miss some errors. No AI detector was used anywhere.
- The SFT side leans formal (abstracts, reports, email).
Citation
@misc{humanizer2026data,
title = {humanizer-data: training data for the humanizer rewriting model (v2)},
author = {Stephen Yu},
year = {2026},
url = {https://huggingface.co/datasets/jialinyyzz/humanizer-data}
}
Please also cite the upstream datasets you use.
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