Datasets:

lm2445
/

FinTagging1000_table

license: mit
task_categories:
  - text-generation
  - token-classification
language:
  - en
tags:
  - finance
  - xbrl
  - numeric-tagging
  - fintagging
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.parquet
      - split: test
        path: data/test.parquet

FinTagging Table Context Extraction Split

For HTML table inputs, the target is a JSON list of numeric entity/datatype pairs enriched with deterministic row and column context. Missing row or column context is represented as null.

The dataset is derived from FinTagging_800_200_HF and preserves the original train/test assignment by source_sample_idx and context_id. The XBRL concept tag is intentionally omitted from the target.

Splits

Split	Samples	Output entries	Duplicate output key groups
train	464	10,831	81
test	110	2,352	11

Columns

source_sample_idx: original source row index.
context_id: original context identifier.
split: original split label.
input_type: table or text.
input: raw table HTML for table data, cleaned plain text for text data.
output: JSON target string.
output_entities: structured version of output.
entity_metadata: deterministic parser metadata for auditing only.

Validation

Check	Value
source sample index overlap	0
context ID overlap	0
passed	True