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FGCS

Introduction

FGCS is a dataset constructed for entity-relation extraction in computer science field. The proposed dataset includes 1,948 sentences of 6 entity types with up to 9 layers of nesting and 5 relation types.

Data format

The dataset is divided into train set (70%), validation set (10%), test set (20%).

train dev test
1364 195 389

Each instance in the dataset is organized as follow:

{
  "tokens": ["We", "start", "from", "analyzing", "the", "procedures", ...],
  "ners": [
    [16, 16, "Metric"], 
    [13, 13, 16, 16, "Metric"],
    ...
  ],
  "relations": [
    [0, 1, "Hyponym-of"],
    ...
  ],
  "discontinuous": true
}

Entries in ners are organized as [token_start, token_end, type] for general entities while [first_span_start, first_span_end, second_span_start, second_span_end, type] for discontinuous entities.

Entries in relations are organized as [head_entity_index, tail_entity_index, type].

discontinuous indicated whether there is a discontinuous entity in this sentence.

Specification

The proposed dataset contains three types of fine-grained entities: nested entities, discontinuous entities and Minimal Independent Semantics (MIS) entities. The statistic of entities and relations is following:

Entities Relations Nested Entities Discontinuous Entities MIS Entities
count 8,559 5,903 3,084 120 652