lm2445/Financial_Tagging_FHS

Evidence-to-Taxonomy Retrieval: FinTagging / US-GAAP 2024 splits

The two splits used in Factorized Hypothesis Search for Evidence-to-Taxonomy Retrieval. Each record is one fact: a value observed in a filing, together with the source context it came from, and the US-GAAP concept(s) a human tagger assigned to it. The task is to retrieve that concept from the 17,388-concept taxonomy given only the context and the value — there is no natural-language query in the input.

file	facts	source contexts	table / text facts	distinct gold concepts	md5
data/test.jsonl	2,509	191	2,341 / 168	388	70b4a0f4dc64ada13c47bdb657a26ce9
data/dev.jsonl	661	70	566 / 95	180	8bfd4c17373d2727187aa10d0c756b8c

How each split was used. Every number reported in the paper is computed on test.jsonl. dev.jsonl is the configuration-selection sample: the number of hypotheses $J$ and the score weight $\beta$ were chosen on it, and it is also the sample behind the appendix tables marked [DEV]. No test fact influenced any configuration choice.

Splits are disjoint at the context level. All facts from one source context stay together, so a context never appears in two splits; the two files share zero context_id values. dev.jsonl carries split: "train" because the development sample is drawn from the training split of the underlying benchmark, not from a separate pool — the field records provenance, not the role the file plays here.

Record schema

Both files use the same schema, except that dev.jsonl adds fact_id (its index within the sample). Fields:

field	type	meaning
context_id	int	source context; the unit to cluster on when bootstrapping
source_sample_idx	int	index of the context in the underlying benchmark
split	str	provenance split of the source context
input_type	str	table or text
input	str	JSON string of input_fields, kept for loaders that want one flat column
input_fields	dict	the parsed context: numeric_entity, datatype, and the row/column or sentence context
ground_truth_concepts	list[str]	gold US-GAAP concept tags
ground_truth_count	int	length of the above
output	str	JSON string of ground_truth_concepts
source_entity_indices	list[int]	where the value occurs in the source context
source_match_statuses	list[str]	how the value was located: exact_cell, exact_sentence, ambiguous_cell, ambiguous_sentence, unmatched
source_occurrence_count	int	number of occurrences found
fact_id	int	dev only: index within the development sample

input / output duplicate input_fields / ground_truth_concepts as JSON strings. They are kept because the runs read them; a loader should prefer the structured fields.

The retrieval index

taxonomy/us_gaap_2024_enriched_retrieval.jsonl (17,388 concepts, ~12 MB, md5 a33ecd6538a11b77d2d6d2fa18fff237) is the index every reported retrieval number is measured against — the taxonomy_jsonl path recorded in all 69 run manifests. One concept per line:

field	type	meaning
tag	str	US-GAAP concept name, without the us-gaap: prefix
type	str	XBRL item type (monetaryItemType, stringItemType, …). This is the datatype the retriever filters on
standard_label	str	readable standard label
documentation	str	documentation label from us-gaap-doc-2024.xml; present for 14,918 of 17,388 concepts
references	list[str]	paragraph-level ASC references from us-gaap-ref-2024.xml; present for 11,888
retrieval_text	str	tag, standard_label and documentation joined — this string, and only this string, is what BM25 indexes

Two things a reader should not have to discover by experiment: references is carried but is not part of retrieval_text, so it never enters the lexical score; and retrieval is restricted to concepts declaring the fact's own type, falling back to the full index when the taxonomy declares none. taxonomy/build_summary.json records the four US-GAAP 2024 source files this was built from and the per-field coverage counts.

Concept counts by type (top): monetary 7,650, string 4,628, domain 1,915, textBlock 982, enumerationSet 569, percent 463.

Provenance

All three files are byte-identical copies (verified by md5) of the files the reported runs read:

• data/test.jsonl — FinTagging_800_200_grounding_test_JSON/data/test.jsonl, the path recorded in the test_jsonl field of all 53 run manifests behind the paper's tables.
• data/dev.jsonl — runs_ags_coverage_pilot/qwen3_32b/sample_facts.jsonl, the default SAMPLE_PATH of the configuration-selection scripts.
• taxonomy/us_gaap_2024_enriched_retrieval.jsonl — retrieval_data/us_gaap_2024_enriched/, the taxonomy_jsonl path recorded in all 69 run manifests.