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nlp2json.py
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| from bs4 import BeautifulSoup | |
| import json | |
| xml = "" | |
| with open("dump/sentences.txt.xml") as input: | |
| xml = input.read() | |
| soup = BeautifulSoup(xml, "xml") | |
| output = {"sentences": [{ | |
| "id": sentence["id"], | |
| "tokens": [{ | |
| "id": token["id"], | |
| "word": token.word.text, | |
| "lemma": token.lemma.text, | |
| "characterOffsetBegin": token.CharacterOffsetBegin.text, | |
| "characterOffsetEnd": token.CharacterOffsetEnd.text, | |
| "pos": token.POS.text, | |
| "ner": token.NER.text | |
| } for token in sentence.find_all("token")], | |
| "parse": sentence.find_all("parse")[0].text, | |
| "dependencies": [{ | |
| "type": dependency["type"], | |
| "dependencies": [{ | |
| "type": sub_dep["type"], | |
| "governor": { | |
| "idx": sub_dep.governor["idx"], | |
| "value": sub_dep.governor.text | |
| }, | |
| "dependent": { | |
| "idx": sub_dep.dependent["idx"], | |
| "value": sub_dep.dependent.text | |
| } | |
| } for sub_dep in dependency.find_all("dep")] | |
| } for dependency in sentence.find_all("dependencies")], | |
| "machineReading": {"entities": [{ | |
| "id": entity["id"], | |
| "val": entity.text.strip(), | |
| "start": entity.span["start"], | |
| "end": entity.span["end"] | |
| } for entity in sentence.find_all("entity")]} | |
| } for sentence in soup.root.document.sentences.find_all("sentence")]} | |
| print json.dumps(output, indent=2) |
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Example output: