Browse State-of-the-Art › Open Information Extraction

Open Information Extraction

67 papers with code · 13 benchmarks · 14 datasets archive 2025-07-28

Natural Language Processing

In natural language processing, open information extraction is the task of generating a structured, machine-readable representation of the information in text, usually in the form of triples or n-ary propositions (Source: Wikipedia).

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

13 leaderboard tables shown for this task, 13 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 13 until expanded.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
CaRB (29 rows) MacroIE A Survey on Neural Open Information Extraction: Current Status and... — — Compare
WiRe57 (18 rows) CIGL-OIE + IGL-CA (OpenIE6) OpenIE6: Iterative Grid Labeling and Coordination Analysis for... code — Compare
OIE2016 (12 rows) DeepEx (zero-shot) Zero-Shot Information Extraction as a Unified Text-to-Triple Translation code — Compare
BenchIE (11 rows) ClausIE BenchIE: A Framework for Multi-Faceted Fact-Based Open Information... code — Compare
LSOIE-wiki (11 rows) SMiLe-OIE Syntactic Multi-view Learning for Open Information Extraction code — Compare
LSOIE (9 rows) DetIELSOIE DetIE: Multilingual Open Information Extraction Inspired by Object... code — Compare
NYT (4 rows) Deepstruct zero-shot DeepStruct: Pretraining of Language Models for Structure Prediction code Syntology ran 7 of 13 samples · 6 unverified Compare
Penn Treebank (4 rows) Deepstruct zero-shot DeepStruct: Pretraining of Language Models for Structure Prediction code Syntology ran 7 of 13 samples · 6 unverified Compare
Web (4 rows) Deepstruct zero-shot DeepStruct: Pretraining of Language Models for Structure Prediction code Syntology ran 7 of 13 samples · 6 unverified Compare
DocOIE-healthcare (2 rows) DocIE w transformer DocOIE: A Document-level Context-Aware Dataset for OpenIE code — Compare
DocOIE-transportation (2 rows) DocIE w transformer DocOIE: A Document-level Context-Aware Dataset for OpenIE code — Compare
CaRB OIE benchmark (Greek Use-case) (1 row) PENELOPIE Greek OIE PENELOPIE: Enabling Open Information Extraction for the Greek... code — Compare
OpenIE (1 row) GEN2OIE (label-rescore) Alignment-Augmented Consistent Translation for Multilingual Open... code — Compare

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

14 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 67 papers with code (207 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections