IndIE: A Multilingual Open Information Extraction Tool For Indic Languages

Abstract

Open Information Extraction (OIE) is the process of extracting informative facts from opendomain natural language text. A multilingual OIE tool, IndIE, has been proposed, which performs chunking, creates a Merged-phrase Dependency Tree (MDT), and generates triples using hand-crafted rules. It is observed that fine-tuned transformer-based chunker outperforms other traditional methods of chunking. A benchmark called Hindi-BenchIE has also been developed for automatically evaluating Hindi triples. The developed OIE tool, IndIE, has been automatically evaluated on the goldentriples of 112 Hindi sentences. Compared to other multilingual methods, the IndIE method generates more meaningful triples with 0.51 F1-score. It is observed that IndIE generates more fine-grained triples than other methods. It is conjectured that IndIE has the ability to generate meaningful triples for Urdu, Tamil, and Telugu sentences as well because the developed chunker is shown to generalize across various natural languages, and the triple generation rules are based on dependency relations that are common to the aforementioned Indic languages.Triple generator algorithm from Merged-phrase Dependency Tree (MDT)Head, T ail ← FIND_HEAD(M DT, t) , t 5:Rel ← x where (x ∈ t.children ∧ x.dep_rel = 'cop') 6: else 7: Head, T ail ← FIND_HEAD(M DT, t) , FIND_TAIL(M DT, t) 8: Rel ← t + x where (x ∈ t.children ∧ x.dep_rel = 'cop') 9: end if 10: else if 'advcl' == t.dep_rel then 11:Head ← q.T ail + q.Rel where (q ∈ Q ∧ t.parent ∈ q) 12:Rel, T ail ← t , FIND_TAIL(M DT, t) 13: else if 'acl' == t.dep_rel then 14:Head ← t.closest_phrase(q.T ail, q.Head) where (q ∈ Q ∧ t.parent ∈ q)