| --- |
| 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). |
|
|
