Crosslingual Coreference
spaCy v3 
Coreference is amazing but the data required for training a model is very scarce. In our case, the available training for non-English languages also data proved to be poorly annotated. Crosslingual Coreference therefore uses the assumption a trained model with English data and cross-lingual embeddings should work for other languages with similar sentence structure. Verified to work quite well for at least (EN, NL, DK, FR, DE).
Example
import spacy text = """ Do not forget about Momofuku Ando! He created instant noodles in Osaka. At that location, Nissin was founded. Many students survived by eating these noodles, but they don't even know him.""" # use any model that has internal spacy embeddings nlp = spacy.load('en_core_web_sm') nlp.add_pipe( "xx_coref", config={"chunk_size": 2500, "chunk_overlap": 2, "device": 0}) ) doc = nlp(text) print(doc._.coref_clusters) # Output # # [[[4, 5], [7, 7], [27, 27], [36, 36]], # [[12, 12], [15, 16]], # [[9, 10], [27, 28]], # [[22, 23], [31, 31]]] print(doc._.resolved_text) # Output # # Do not forget about Momofuku Ando! # Momofuku Ando created instant noodles in Osaka. # At Osaka, Nissin was founded. # Many students survived by eating instant noodles, # but Many students don't even know Momofuku Ando.
Categories pipeline standalone
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