ucrelnlp/PyMUSAS-Neural-English-Small-BEM
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Datasets:
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English USAS Mosaico Dataset
Note that this dataset cannot be loaded using the HuggingFace datasets library as we have 2 data types within a list in the pos column, however you can download the dataset and load it within Python using the json and gzip core modules, an example loading script can be found at ./example_loading_script.py.
This dataset contains the processed English Wikipedia pages of the Mosaico dataset, of which this is a subset of the original English Wikipedia dataset whereby it contains only the pages with the tags good and featured.
Each entry in the dataset is a processed Wikipedia page containing the following annotations/tags:
- Sentence boundaries
- Tokens
- Lemmas
- Part Of Speech (POS) tags - CLAWS 7 tagset
- USAS tags - These are semantic tags that have come from the USAS tagset.
These annotations have been added automatically using the C version of the CLAWS and USAS tagger, both of these taggers are not freely available (not open source) but the documentation detailing how they were created and what tags they output are at the given links, if you would like to know more about the taggers or would like to use them please get in contact with us (an open source version of English USAS tagger can be found within the PyMUSAS framework).
- Curated by: University Centre for Computer Corpus Research on Language (UCREL) group at Lancaster University
- Language: English
- License: CC-BY-NC-SA 4.0
- Repository: https://github.com/UCREL/mosaico-usas-processing
- Number of Samples Contains 10,779 samples whereby each one represents a Wikipedia page.
For more details about this dataset and how it was processed see the GitHub repository.
Uses
This dataset can be used to train, in a semi-supervised manner, a POS tagger or a Semantic tagger.
Dataset Structure
Example Wikipedia page, a lot of the data has been removed, e.g. the text is only the first 15 or so words. Each sample in the dataset is one Wikipedia page. The full schema is shown below this example.
{
"document_id": "3021080",
"wikidata_id": "Q921355",
"title": "Erik Adolf von Willebrand",
"text": "Erik Adolf von Willebrand (1 February 1870 \u2013 12 September 1949) was a Finnish physician ...",
"ascii_text": "Erik Adolf von Willebrand (1 February 1870 - 12 September 1949) was a Finnish physician ...",
"language": "en",
"quality": "good",
"ores_articletopics": {
"Geography.Regions.Europe.Northern Europe": 0.584,
"Culture.Biography.Biography*": 0.983,
"Geography.Regions.Europe.Europe*": 0.857,
"STEM.STEM*": 0.983
},
"categories": [
"CS1 Swedish-language sources (sv)",
"CS1 Finnish-language sources (fi)",
"CS1: long volume value",
"Good articles",
"Articles with short description",
"Short description is different from Wikidata",
"Use dmy dates from July 2018",
"Articles with hCards",
"CS1 German-language sources (de)",
"CS1 errors: missing periodical",
"CS1 Dutch-language sources (nl)",
"AC with 0 elements",
"1870 births",
"1949 deaths",
"Academics of the University of Helsinki",
"Finnish hematologists",
"Finnish people of German descent",
"People from Vaasa",
"Swedish-speaking Finns",
"University of Helsinki alumni",
"20th-century Finnish physicians"
],
"popularity_score": 8.327128616319467e-08,
"timestamp": "2021-12-26T18:49:13Z",
"tokens": [
"Erik",
"Adolf",
"von",
"Willebrand",
"(",
"1",
"February",
"1870",
"-",
"12",
"September",
"1949",
")",
"was",
"a",
"Finnish",
"physician",
"who"
],
"lemmas": [
"erik",
"adolf",
"von",
"willebrand",
"PUNC",
"1",
"february",
"1870",
"PUNC",
"12",
"september",
"1949",
"PUNC",
"be",
"a"
],
"pos": [
[
[
"NP1",
100
]
],
[
[
"NP1",
100
]
],
[
[
"NP1",
100
]
],
[
[
"NP1",
100
]
],
[
[
"(",
100
]
],
[
[
"MC1",
100
]
],
[
[
"NPM1",
100
]
],
[
[
"MC",
100
]
],
[
[
"-",
100
]
],
[
[
"MC",
100
]
]
],
"usas": [
[
{
"tags": [
{
"tag": "Z1",
"number_positive_markers": 0,
"number_negative_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"female": true,
"male": true,
"antecedents": false,
"neuter": false,
"idiom": false
}
]
},
{
"tags": [
{
"tag": "Z3",
"number_positive_markers": 0,
"number_negative_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"female": false,
"male": false,
"antecedents": true,
"neuter": false,
"idiom": false
}
]
},
{
"tags": [
{
"tag": "Z1",
"number_positive_markers": 0,
"number_negative_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"female": false,
"male": true,
"antecedents": false,
"neuter": false,
"idiom": false
}
]
},
{
"tags": [
{
"tag": "Z1",
"number_positive_markers": 0,
"number_negative_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"female": true,
"male": true,
"antecedents": false,
"neuter": false,
"idiom": false
}
]
},
{
"tags": [
{
"tag": "Z3",
"number_positive_markers": 0,
"number_negative_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"female": false,
"male": false,
"antecedents": true,
"neuter": false,
"idiom": false
}
]
}
]
],
"usas_raw": [
"Z1mf[i2.3.1 Z3c[i2.3.1 Z1m Z1mf[i1.2.1 Z3c[i1.2.1",
"Z1mf[i2.3.2 Z3c[i2.3.2 Z1mf[i4.3.1 Z3c[i4.3.1 Z1m Z1mf[i1.2.2 Z3c[i1.2.2 Z1mf[i3.2.1 Z3c[i3.2.1"
],
"sentence_boundaries": [
[
0,
24
],
[
24,
36
]
]
}
The only keys that are not explained in the schema below are the following:
lemmas- A list of lemmas one per token.pos- These are a list of POS tags, one tag per token. Each tag is made up of a list/tuple of length 2:- POS tag, e.g.
NPM1 - Confidence - 0-100 confidence of predicting this tag, 100 is very confident 0 is not confident.
- POS tag, e.g.
usas- A list ofUSASTagGroups, one USAS Tag Group per token. A USAS Tag Group is a formatted version of theusas_rawoutput.usas_raw- The raw non formatted version ofusas, one per token.sentence_boundaries- A list of tuples, each tuple represents the token boundaries of a sentence. For instancetokens[sentence_boundaries[0][0]: sentence_boundaries[0][1]]represents the tokens of the first sentence.
{
"USASTag": {
"description": "Represents all of the properties associated with a USAS tag.",
"properties": {
"tag": {
"description": "USAS Tag",
"examples": [
"A1.1.1"
],
"title": "USAS Tag",
"type": "string"
},
"number_positive_markers": {
"default": 0,
"description": "Number of positive markers.",
"examples": [
0,
1,
2,
3
],
"title": "Positive Markers",
"type": "integer"
},
"number_negative_markers": {
"default": 0,
"description": "Number of negative markers.",
"examples": [
0,
1,
2,
3
],
"title": "Negative Markers",
"type": "integer"
},
"rarity_marker_1": {
"default": false,
"description": "Rarity marker 1 indicated by %",
"title": "Rare Marker 1",
"type": "boolean"
},
"rarity_marker_2": {
"default": false,
"description": "Rarity marker 2 indicated by @",
"title": "Rare Marker 2",
"type": "boolean"
},
"female": {
"default": false,
"description": "Female",
"title": "Female",
"type": "boolean"
},
"male": {
"default": false,
"description": "Male",
"title": "Male",
"type": "boolean"
},
"antecedents": {
"default": false,
"description": "Potential antecedents of conceptual anaphors (neutral for number)",
"title": "Antecedents",
"type": "boolean"
},
"neuter": {
"default": false,
"description": "Neuter",
"title": "Neuter",
"type": "boolean"
},
"idiom": {
"default": false,
"description": "Is it an idiom",
"title": "Idiom",
"type": "boolean"
}
},
"required": [
"tag"
]
},
"USASTagGroup": {
"description": "Represents a grouping of one or more USAS tags that are associated to a token.",
"properties": {
"tags": {
"description": "A grouping of one or more USAS tags whereby if more than one exists then the word is an equal member of all semantic tags/categories",
"examples": [
[
{
"antecedents": false,
"female": false,
"idiom": false,
"male": false,
"neuter": false,
"number_negative_markers": 0,
"number_positive_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"tag": "A1.1.1"
}
],
[
{
"antecedents": false,
"female": false,
"idiom": false,
"male": false,
"neuter": false,
"number_negative_markers": 1,
"number_positive_markers": 0,
"rarity_marker_1": false,
"rarity_marker_2": false,
"tag": "E2"
},
{
"antecedents": false,
"female": false,
"idiom": false,
"male": false,
"neuter": false,
"number_negative_markers": 0,
"number_positive_markers": 1,
"rarity_marker_1": false,
"rarity_marker_2": false,
"tag": "S7.1"
}
]
]
}
},
"required": [
"tags"
]
}
},
"properties": {
"document_id": {
"description": "ID that uniquely represents that document within the Mosaico Mongo DB",
"examples": [
"3021080"
],
"title": "Document ID",
"type": "string"
},
"wikidata_id": {
"description": "Wikidata ID, every Wikipedia page should one as it is an unique ID that allows you to access it's global unique URL https://www.wikidata.org/entity/ID",
"examples": [
"Q921355"
],
"title": "Wikidata ID",
"type": "string"
},
"title": {
"description": "Wikipedia page title",
"examples": [
"Erik Adolf von Willebrand"
],
"title": "Title",
"type": "string"
},
"text": {
"description": "The UTF-8 encoded Wikipedia article text",
"title": "Text",
"type": "string"
},
"ascii_text": {
"description": "ASCII encoded version of the Wikipedia article text",
"title": "ASCII Text",
"type": "string"
},
"language": {
"const": "en",
"description": "Language of the Wikipedia article",
"examples": [
"en"
],
"title": "Language",
"type": "string"
},
"quality": {
"description": "Quality of the Wikipedia page as determined by the Wikipedia community",
"enum": [
"good",
"featured"
],
"examples": [
"good",
"featured"
],
"title": "Quality",
"type": "string"
},
"ores_articletopics": {
"additionalProperties": {
"type": "number"
},
"description": "High level article topics that are easily searchable and have been predicted by a machine learning model. This will be represented as a dictionary of topic and score whereby the score is between 0-1 where 1 indicates the model is more confident of it's prediction.",
"examples": [
{
"Geography.Regions.Europe.Northern Europe": 0.584
}
],
"title": "ORES article topics",
"type": "object"
},
"categories": {
"description": "A noisy list of article topics that are found on the Wikipedia page at the end. To note that the hierarchy of this category system can be found through the SQL database dumps according to this source. The reason these are noisy is that they sometimes contain meta data topics like `CS1 Swedish-language sources (sv)` or `Good articles`.",
"examples": [
[
"CS1 Swedish-language sources (sv)",
"AC with 0 elements",
"1870 births",
"1949 deaths",
"Academics of the University of Helsinki",
"Finnish hematologists",
"Finnish people of German descent",
"People from Vaasa"
]
],
"items": {
"type": "string"
},
"title": "Categories",
"type": "array"
},
"popularity_score": {
"anyOf": [
{
"type": "number"
},
{
"type": "null"
}
],
"description": "As defined in the cirrus schema, 'A floating point number representing the percentage of page views to this wiki that requests this page. This is only available for content pages.' If the popularity score cannot be validated or found it will have a value of `None`.",
"examples": [
8.327128616319467e-08,
null
],
"title": "Popularity Score"
},
"timestamp": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"description": "Timestamp of the most recently index/edited version of the page. If the timestamp cannot be found it will have a value of `None`.",
"examples": [
"2021-12-26T18:49:13Z",
null
],
"title": "timestamp"
},
"tokens": {
"items": {
"type": "string"
},
"title": "Tokens",
"type": "array"
},
"lemmas": {
"items": {
"type": "string"
},
"title": "Lemmas",
"type": "array"
},
"pos": {
"items": {
"items": {
"maxItems": 2,
"minItems": 2,
"prefixItems": [
{
"type": "string"
},
{
"type": "integer"
}
],
"type": "array"
},
"type": "array"
},
"title": "POS",
"type": "array"
},
"usas": {
"items": {
"items": {
"$ref": "#/$defs/USASTagGroup"
},
"type": "array"
},
"title": "USAS",
"type": "array"
},
"usas_raw": {
"items": {
"type": "string"
},
"title": "USAS Raw",
"type": "array"
},
"sentence_boundaries": {
"items": {
"maxItems": 2,
"minItems": 2,
"prefixItems": [
{
"type": "integer"
},
{
"type": "integer"
}
],
"type": "array"
},
"title": "Sentence Boundaries",
"type": "array"
}
},
"required": [
"document_id",
"wikidata_id",
"title",
"text",
"ascii_text",
"language",
"quality",
"ores_articletopics",
"categories",
"popularity_score",
"timestamp",
"tokens",
"lemmas",
"pos",
"usas",
"usas_raw",
"sentence_boundaries"
],
"title": "TaggedWikiDataExport",
"type": "object"
}
Dataset Card Authors
- UCREL ([email protected])
- Andrew Moore / apmoore1 ([email protected] / [email protected])
- Paul Rayson ([email protected])
Dataset Card Contact
- UCREL ([email protected])
- Andrew Moore / apmoore1 ([email protected] / [email protected])
- Paul Rayson ([email protected])
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