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							05438d7
								
Upload lampeter_corpus.py
Browse filesChanged date to datasets.Value("date64")
- lampeter_corpus.py +31 -24
    	
        lampeter_corpus.py
    CHANGED
    
    | @@ -19,6 +19,7 @@ areas of everyday life and, last but not least, the standardisation of British E | |
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            from bs4 import BeautifulSoup
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            import datasets
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            _CITATION = """ @misc{20.500.12024/3193,
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             title = {The Lampeter Corpus of Early Modern English Tracts},
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| @@ -39,7 +40,15 @@ _LICENSE = "Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)" | |
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            _URL = "https://ota.bodleian.ox.ac.uk/repository/xmlui/bitstream/handle/20.500.12024/3193/3193.xml?sequence=9&isAllowed=y"
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            _CLASS_MAP = { | 
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            class LampeterCorpus(datasets.GeneratorBasedBuilder):
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                """ The Lampeter Corpus of Early Modern English Tracts is a collection of texts on
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| @@ -54,10 +63,10 @@ class LampeterCorpus(datasets.GeneratorBasedBuilder): | |
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                        {
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                            "id": datasets.Value("string"),
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                            "text": datasets.Value("string"),
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                            "date": datasets.Value(" | 
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                            "genre": datasets.Value("string"),
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                            "head": datasets.Value("string"),
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                            "title": datasets.Value("string")
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                        }
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                    )
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                    return datasets.DatasetInfo(
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| @@ -73,40 +82,38 @@ class LampeterCorpus(datasets.GeneratorBasedBuilder): | |
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                    return [
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                        datasets.SplitGenerator(
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                            name=datasets.Split.TRAIN,
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                            gen_kwargs={
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                                "split": "train",
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                            },
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                        ),      
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                    ]
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                def _generate_examples(self, filepath, split):
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                    with open(filepath, encoding="utf-8") as f:
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                        soup=BeautifulSoup(f, features= | 
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                        for entry in soup.find_all("TEI"):
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                            text_parts = []
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                            title_with_id = entry.teiHeader.fileDesc.titleStmt.title.text
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                            id, title = title_with_id.split(":", maxsplit=1)
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                            id = id.strip()
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                            title=title.strip()
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                            date=id[-4:]
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                            content = entry.find("text")
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                            head=content.find("body").find("head")
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                            if head:
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                                head=head.text
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                            else:
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                                head=""
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                            body_parts=content.find("body").find_all("p")
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                            for body_part in body_parts:
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                                text_parts.append(body_part.text)
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                            full_text = " ".join(text_parts)
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                            genre=_CLASS_MAP[id[0]]
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                            data_point = {
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                                "id": id, | 
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                                "text": full_text, | 
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                                "genre": genre, | 
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                                "date": date, | 
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                                "head": head, | 
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                                "title": title
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                            yield id, data_point
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            from bs4 import BeautifulSoup
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            import datasets
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            from datetime import datetime
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            _CITATION = """ @misc{20.500.12024/3193,
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             title = {The Lampeter Corpus of Early Modern English Tracts},
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            _URL = "https://ota.bodleian.ox.ac.uk/repository/xmlui/bitstream/handle/20.500.12024/3193/3193.xml?sequence=9&isAllowed=y"
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            _CLASS_MAP = {
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                "L": "Law",
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                "E": "Economy",
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                "M": "Miscellaneous",
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                "P": "Politics",
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                "S": "Science",
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                "R": "Religion",
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            }
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             | 
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            class LampeterCorpus(datasets.GeneratorBasedBuilder):
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                """ The Lampeter Corpus of Early Modern English Tracts is a collection of texts on
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                        {
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                            "id": datasets.Value("string"),
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                            "text": datasets.Value("string"),
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                            "date": datasets.Value("date64"),
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                            "genre": datasets.Value("string"),
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                            "head": datasets.Value("string"),
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                            "title": datasets.Value("string"),
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                        }
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                    )
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                    return datasets.DatasetInfo(
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                    return [
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                        datasets.SplitGenerator(
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                            name=datasets.Split.TRAIN,
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                            gen_kwargs={"filepath": data_file, "split": "train",},
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                        ),
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                    ]
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                def _generate_examples(self, filepath, split):
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                    dt_format = "%Y"
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                    with open(filepath, encoding="utf-8") as f:
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                        soup = BeautifulSoup(f, features="xml")
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                        for entry in soup.find_all("TEI"):
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                            text_parts = []
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                            title_with_id = entry.teiHeader.fileDesc.titleStmt.title.text
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                            id, title = title_with_id.split(":", maxsplit=1)
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                            id = id.strip()
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                            title = title.strip()
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                            date = datetime.strptime(id[-4:], dt_format)
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                            content = entry.find("text")
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                            head = content.find("body").find("head")
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                            if head:
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                                head = head.text
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                            else:
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                                head = ""
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                            body_parts = content.find("body").find_all("p")
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                            for body_part in body_parts:
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                                text_parts.append(body_part.text)
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                            full_text = " ".join(text_parts)
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                            genre = _CLASS_MAP[id[0]]
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                            data_point = {
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                                "id": id,
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                                "text": full_text,
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                                "genre": genre,
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                                "date": date,
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                                "head": head,
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                                "title": title,
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            +
                            }
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            +
                            yield id, data_point
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