---
license: cc-by-nc-sa-4.0
language: [en]
size_categories: [100K<n<1M]
task_categories: [question-answering, text-retrieval]
tags: [scientometrics, affiliations, ror, acl-anthology, cso, bibliometrics]
configs:
  - config_name: papers
    data_files: papers/*.parquet
  - config_name: affiliations
    data_files: affiliations/*.parquet
  - config_name: topics
    data_files: topics/*.parquet
  - config_name: fulltext
    data_files: fulltext/*.parquet
  - config_name: affiliation_gold
    data_files: affiliation_gold/*.parquet
  - config_name: benchmark_questions
    data_files: benchmark_questions/*.parquet
  - config_name: cso_validation
    data_files: cso_validation/*.parquet
  - config_name: linking_adjudication
    data_files: linking_adjudication/*.parquet
  - config_name: lora_train
    data_files:
      - split: train
        path: lora_train/train-*.parquet
      - split: validation
        path: lora_train/validation-*.parquet
---

# ANTHEM-202605 — an Enriched ACL Anthology for Scholarly Comparison

117,386 ACL Anthology papers linked to ROR-normalised author affiliations
and Computer Science Ontology (CSO) topic labels, with an evidence span
retained for every extraction decision.

Code: <https://github.com/MoritzStaudinger/anthem>

## Configs

| Config | Rows | What |
|---|---:|---|
| `papers` | 117,386 | one row per paper; nested fields kept as JSON strings |
| `affiliations` | 516,008 | flat: paper x author x affiliation, with ROR id and evidence |
| `topics` | 1,447,513 | flat: paper x CSO label, `source` = syntactic \| semantic |
| `fulltext` | 117,379 | parsed text per paper: GROBID TEI, PyMuPDF/LLM Markdown, OCR |
| `affiliation_gold` | 781 | hand-annotated affiliation gold set (781 papers) |
| `benchmark_questions` | 99 | comparative-QA benchmark: question, persona, the ROR/topic/year gold specification, and the resolved `gold_paper_ids` |
| `cso_validation` | 104 | hand-judged CSO topic labels |
| `linking_adjudication` | 805 | hand-verified ROR linking decisions, four strategies side by side |
| `lora_train` | 10,000 | LoRA fine-tuning data for the affiliation adapter (`train` / `validation` splits) |

Nested structures are stored as JSON strings because record shape varies across
1952--2025; the flat `affiliations` and `topics` configs are the ones to query.

```python
from datasets import load_dataset

aff = load_dataset("Molarix/anthem", "affiliations", split="train")
```

`fulltext` is the large config — load it only when you need the text itself.

## Licensing

ANTHEM's own layer — the extracted affiliations, ROR links, CSO labels and
evidence spans in `papers`, `affiliations` and `topics` — is released under
**CC-BY-NC-SA-4.0**.

The `license` column is provenance, not the release licence: it records the
terms the underlying paper carries in the Anthology. Per the
[ACL Anthology copyright policy](https://aclanthology.org/faq/copyright/),
materials prior to 2016 are CC BY-NC-SA 3.0 and materials from 2016 onward are
CC BY 4.0. Papers whose year could not be determined are assigned the more
restrictive pre-2016 term.

9,470 papers were published at third-party (ELRA-published) venues such as LREC. The ACL copyright policy states that it does not cover third-party materials, so these rows carry `third_party_venue = true`; filter on it if your use needs only ACL-licensed material.

Source PDFs are not redistributed; the Anthology serves those. `fulltext`
contains parsed renderings (TEI, Markdown, OCR text) produced by this pipeline.

| Underlying licence | Papers |
|---|---:|
| CC-BY-4.0 | 69,297 |
| CC-BY-NC-SA-3.0 | 38,618 |
| third-party venue (ELRA-published); see respective organisation | 9,471 |

## Construction

Affiliations were extracted from parsed PDFs by an LLM pipeline over combined
parser outputs (GROBID TEI + PyMuPDF/LLM Markdown + OCR), then linked to ROR
with country context. The model recorded per paper:

| `provenance_model` | Papers |
|---|---:|
| gemini-2.5-flash | 79,666 |
| gemini-2.5-flash-lite | 22,261 |
| gemini-1.5-flash | 15,449 |
| None | 10 |

## Personal and sensitive information

The dataset joins author names to institutions and publication years. All of it
is already public in the ACL Anthology, and affiliations are as printed at
publication time rather than current.

The `fulltext` config is a faithful parse of the published PDFs, so where a paper printed author e-mail addresses in its header, the TEI and OCR text contain them too. They are not separated into a column, and no contact details beyond what the papers themselves print are added.

## Known limitations

Affiliation extraction and linking reach F1 0.760 (hierarchy-aware, parent and
child ROR ids treated as equivalent) against a 781-paper decade-stratified gold
set; ROR linking alone reaches 0.857 on hand-checked affiliation strings; CSO
topic-label precision is 0.713. Roughly 90% of remaining false negatives are
linking rather than extraction failures, concentrated in city-level institution
clusters and geographically branched corporate entities.

This is a fixed snapshot (ANTHEM-202605); it is not updated in place.

## Citation

Please cite the ANTHEM paper; the current reference is kept in the
[code repository](https://github.com/MoritzStaudinger/anthem).