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Datasets:
ShkalikovOleh
/
europarl-ner

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Token Classification
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parquet
Languages:
English
Italian
German
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1K - 10K
Tags:
NER
Europarl
named-entity-recognition
annotation-projection
XLNER
cross-lingual-ner
Libraries:
Datasets
pandas
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70
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70
[ "Resumption", "of", "the", "session" ]
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[ "Madam", "President", ",", "on", "a", "point", "of", "order", "." ]
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[ "You", "will", "be", "aware", "from", "the", "press", "and", "television", "that", "there", "have", "been", "a", "number", "of", "bomb", "explosions", "and", "killings", "in", "Sri", "Lanka", "." ]
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[ "Thank", "you", ",", "Mr", "Segni", ",", "I", "shall", "do", "so", "gladly", "." ]
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[ "Thank", "you", ",", "Mr", "Poettering", "." ]
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[ "We", "shall", "now", "hear", "Mr", "Wurtz", "speaking", "against", "this", "request", "." ]
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[ "It", "is", "not", "a", "lot", "to", "ask", "." ]
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[ "Thank", "you", "very", "much", "." ]
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[ "My", "vote", "was", "\"", "in", "favour", "\"", "." ]
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[ "Madam", "President", ",", "the", "Presidency", "has", "already", "declared", "the", "result", "of", "the", "vote", "." ]
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[ "There", "is", "no", "room", "for", "amendments", "." ]
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[ "I", "would", "appreciate", "it", "if", ",", "on", "the", "close", "of", "this", "item", "of", "business", ",", "I", "might", "be", "allowed", "to", "give", "an", "explanation", "of", "vote", "on", "behalf", "of", "my", "Group", "." ]
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[ "Madam", "President", ",", "I", "do", "not", "wish", "to", "reopen", "the", "debate", ",", "but", "I", "had", "also", "asked", "for", "the", "floor", ",", "to", "comment", "on", "Mr", "Barón", "Crespo", "'s", "motion", "." ]
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[ "You", "did", "not", "call", "me", "either", "." ]
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[ "I", "regret", "this", ",", "but", "the", "vote", "has", "already", "been", "taken", "and", "the", "decision", "is", "made", "so", "let", "us", "leave", "the", "matter", "there", "." ]
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[ "Even", "so", ",", "I", "think", "the", "positions", "are", "quite", "clear", "and", "they", "shall", "be", "entered", "in", "the", "Minutes", "." ]
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[ "When", "we", "adopt", "the", "Minutes", "for", "today", "'", "s", "sitting", "tomorrow", ",", "then", "any", "Members", "who", "think", "the", "positions", "have", "not", "been", "explained", "clearly", "enough", "may", "ask", "for", "amendments", "." ]
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[ "This", "seems", "to", "me", "to", "be", "a", "workable", "solution", "." ]
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[ "Of", "course", ",", "the", "Minutes", "for", "tomorrow", "'", "s", "sitting", "will", "take", "into", "account", "any", "additional", "explanations", "." ]
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[ "Mr", "Cox", ",", "Mr", "Hänsch", ",", "would", "this", "be", "acceptable", "to", "you", "?" ]
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[ "Madam", "President", ",", "if", "the", "vote", "records", "correctly", "how", "my", "Group", "voted", "I", "shall", "not", ",", "and", "cannot", ",", "object", "to", "that", "." ]
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[ "If", "your", "ruling", "is", "that", "I", "cannot", "give", "an", "explanation", "of", "vote", ",", "I", "accept", "that", "but", "with", "reservations", "." ]
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[ "Safety", "advisers", "for", "the", "transport", "of", "dangerous", "goods" ]
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[ "As", "an", "Austrian", ",", "I", "still", "have", "a", "vivid", "memory", ",", "as", ",", "I", "believe", ",", "we", "all", "do", ",", "of", "the", "catastrophe", "which", "cost", "so", "many", "human", "lives", "last", "year", "in", "the", "Tauern", "Tunnel", ",", "where", "subsequent", "work", "to", "rebuild", "the", "parts", "of", "the", "tunnel", "which", "had", "been", "destroyed", "in", "this", "fire", "continued", "for", "many", "months", "at", "huge", "expense", "." ]
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[ "The", "renovation", "project", ",", "which", "lasted", "for", "months", ",", "cut", "off", "this", "important", "route", "between", "the", "north", "and", "south", "of", "Europe", "." ]
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[ "The", "traffic", "which", "had", "to", "be", "diverted", "because", "of", "this", "stretched", "the", "patience", "of", "many", "thousands", "of", "people", "in", "the", "EU", "to", "the", "limit", "." ]
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[ "In", "fact", ",", "all", "hell", "broke", "loose", "in", "some", "municipalities", "in", "my", "province", "." ]
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Dataset Card for Europarl-ner

This dataset is an adapted to HF datasets copy of "Evaluation Corpus for Named Entity Recognition using Europarl" available on GitHub

Dataset Description

Dataset Summary

This dataset consists of parallel sentences labeled with CONLL2003 tags, which allows use it for the evaluation of cross-lingual annotation projection methods for cross lingual named entity recognition.

Original description

This dataset contains a gold-standard test set created from the Europarl corpus. The test set consists of 799 sentences manually annotated using four entity types and following the CoNLL 2002 and 2003 guidelines for 4 languages: English, German, Italian and Spanish.

If you use this corpus for your research, please cite the following publication:

Rodrigo Agerri, Yiling Chung, Itziar Aldabe, Nora Aranberri, Gorka Labaka and German Rigau (2018). Building Named Entity Recognition Taggers via Parallel Corpora. In Proceedings of the 11th Language Resources and Evaluation Conference (LREC 2018), 7-12 May, 2018, Miyazaki, Japan.

You should also consider citing the original Europarl publication:

Europarl: A Parallel Corpus for Statistical Machine Translation, Philipp Koehn, MT Summit 2005.

This evaluation corpus was manually annotated by Nora Aranberri.

Languages

The dataset contains 4 languages, one in each of the configuration subsets:

  • en - English
  • de - German
  • es - Spanish
  • it - Italian

Dataset Structure

Data Instances

This is an example in the "test" split of the "en" (English language) configuration subset:

{
  'tokens': ["Thank", "you", ",", "Mr", "Segni", ",", "I", "shall", "do", "so", "gladly", "."],
  'ner_tags': [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
}

Data Fields

  • tokens: a list of string features.
  • ner_tags: a list of classification labels, with possible values including O (0), B-PER (1), I-PER (2), B-ORG (3), I-ORG (4), B-LOC (5), I-LOC (6), B-MISC (7), I-MISC (8),

Data Splits

Every subset contains only a test split with 799 rows.

Additional Information

Licensing Information

The citation from the original repo:

We follow the original Europarl terms of use which states : "We are not aware of any copyright restrictions of the material." For more details, please visit http://www.statmt.org/europarl/

Citation Information

Authors ask to cite the following publications:

@inproceedings{agerri-etal-2018-building,
    title = "Building Named Entity Recognition Taggers via Parallel Corpora",
    author = "Agerri, Rodrigo  and
      Chung, Yiling  and
      Aldabe, Itziar  and
      Aranberri, Nora  and
      Labaka, Gorka  and
      Rigau, German",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Hasida, Koiti  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios  and
      Tokunaga, Takenobu",
    booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)",
    month = may,
    year = "2018",
    address = "Miyazaki, Japan",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L18-1557"

@inproceedings{koehn2005europarl,
  title={Europarl: A parallel corpus for statistical machine translation},
  author={Koehn, Philipp},
  booktitle={Proceedings of machine translation summit x: papers},
  pages={79--86},
  year={2005}
}
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