PulseBench-Tab: A Multilingual Benchmark for Table Extraction with Graph-Based Evaluation
We introduce PulseBench-Tab, an open multilingual benchmark for evaluating table extraction from document images. The benchmark comprises 1,820 human-annotated tables spanning 9 languages and 4 scripts (Latin, CJK, Arabic, Cyrillic), drawn from 380 real-world source documents including financial filings, government reports, and regulatory disclosures. Tables range from 2 to 1,183 cells, with 48.1% containing merged or spanning cells. Alongside the dataset, we propose T-LAG (Table Logical Adjacency Graph), a novel evaluation metric that models tables as directed graphs over cell adjacencies and computes structural and content fidelity in a single score via optimal bipartite matching. We evaluate 9 commercial and open-source table extraction systems across the benchmark and report per-language breakdowns. The full dataset, scoring code, and all provider outputs are publicly available.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Benchmarking Large Language Models on Reference Extraction and Parsing in the Social Sciences and Humanities
Bibliographic reference extraction and parsing are foundational for citation indexing, linking, and downstream scholarly knowledge-graph construction. However, most established evaluations focus on clean, English, end-of…
Event Guided Denoising for Multilingual Relation Learning
General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that produces state-of-the-art results across man…
ArticlesDenoisingRelationRelation ExtractionEvent-Guided Denoising for Multilingual Relation Learning
General purpose relation extraction has recently seen considerable gains in part due to a massively data-intensive distant supervision technique from Soares et al. (2019) that produces state-of-the-art results across man…
ArticlesDenoisingRelationRelation ExtractionLLM-based Atomic Propositions help weak extractors: Evaluation of a Propositioner for triplet extraction
Knowledge Graph construction from natural language requires extracting structured triplets from complex, information-dense sentences. In this paper, we investigate if the decomposition of text into atomic propositions (m…
Knowledge DistillationRelation ExtractionLOME: Large Ontology Multilingual Extraction
We present LOME, a system for performing multilingual information extraction. Given a text document as input, our core system identifies spans of textual entity and event mentions with a FrameNet (Baker et al., 1998) par…
coreference-resolutionCoreference ResolutionEntity TypingRelation+3