2

我正在尝试将我的 spacy 版本升级到 nightly 特别是对于使用 spacy 变压器

所以我转换了spacy简单的火车数据集，格式如下

td = [["Who is Shaka Khan?", {"entities": [(7, 17, "FRIENDS")]}],["I like London.", {"entities": [(7, 13, "LOC")]}],]

以上到

[[{"head": 0, "dep": "", "tag": "", "orth": "Who", "ner": "O", "id": 0}, {"head": 0, "dep": "", "tag": "", "orth": "is", "ner": "O", "id": 1}, {"head": 0, "dep": "", "tag": "", "orth": "Shaka", "ner": "B-FRIENDS", "id": 2}, {"head": 0, "dep": "", "tag": "", "orth": "Khan", "ner": "L-FRIENDS", "id": 3}, {"head": 0, "dep": "", "tag": "", "orth": "?", "ner": "O", "id": 4}], [{"head": 0, "dep": "", "tag": "", "orth": "I", "ner": "O", "id": 0}, {"head": 0, "dep": "", "tag": "", "orth": "like", "ner": "O", "id": 1}, {"head": 0, "dep": "", "tag": "", "orth": "London", "ner": "U-LOC", "id": 2}, {"head": 0, "dep": "", "tag": "", "orth": ".", "ner": "O", "id": 3}]]

使用以下脚本

sentences = []
for t in td:
    doc = nlp(t[0])
    tags = offsets_to_biluo_tags(doc, t[1]['entities'])
    ner_info = list(zip(doc, tags))
    tokens = []
    for n, i in enumerate(ner_info):
        token = {"head" : 0,
        "dep" : "",
        "tag" : "",
        "orth" : i[0].orth_,
        "ner" : i[1],
        "id" : n}
        tokens.append(token)
    sentences.append(tokens)



with open("train_data.json","w") as js:
    json.dump(sentences,js)```


then i tried to convert this train_data.json using 
spacy's convert command

```python -m spacy convert train_data.json converted/```


but the result in converted folder is

```✔ Generated output file (0 documents): converted/train_data.spacy``` 

which means it doesn't created dataset

can anybody help on what i am missing

i am trying to do this with spacy-nightly
4

1 回答 1

4

您可以跳过中间 JSON 步骤并将注释直接转换为DocBin.

import spacy
from spacy.training import Example
from spacy.tokens import DocBin

td = [["Who is Shaka Khan?", {"entities": [(7, 17, "FRIENDS")]}],["I like London.", {"entities": [(7, 13, "LOC")]}],]

nlp = spacy.blank("en")
db = DocBin()

for text, annotations in td:
    example = Example.from_dict(nlp.make_doc(text), annotations)
    db.add(example.reference)

db.to_disk("td.spacy")

请参阅：https ://nightly.spacy.io/usage/v3#migrating-training-python

（如果您确实想使用中间 JSON 格式，请参考以下规范：https ://spacy.io/api/annotation#json-input 。您可以只包含orthandner并tokens忽略其他功能，但您需要这个结构带有paragraphs,raw和sentences. 一个例子在这里：https ://github.com/explosion/spaCy/blob/45c9a688285081cd69faa0627d9bcaf1f5e799a1/examples/training/training-data.json ）

于 2020-11-04T10:03:01.037 回答