Datasets:
tokens_a
sequence | tokens_b
sequence | labels_a
sequence | labels_b
sequence | lang_a
stringclasses 1
value | lang_b
stringclasses 1
value | subset
stringclasses 2
values | id
stringlengths 1
3
| alignments
stringlengths 267
2.27k
|
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[
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"camp",
"guard",
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[
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[
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[
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] | en | en | headlines | 5 | [{"sent1_word_ids": [3], "sent2_word_ids": [0], "type": "NOALI", "score": 0.0, "comment": "denies <==> -not aligned- "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [1], "type": "EQUI_POL", "score": 5.0, "comment": "Syrian regime <==> Syria "}, {"sent1_word_ids": [4], "sent2_word_ids": [0], "type": "NOALI", "score": 0.0, "comment": "role <==> -not aligned- "}, {"sent1_word_ids": [0], "sent2_word_ids": [7, 8, 9], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> of over 100 "}, {"sent1_word_ids": [5, 6, 7], "sent2_word_ids": [4, 5, 6], "type": "EQUI", "score": 5.0, "comment": "in Houla massacre <==> for Houla massacre "}, {"sent1_word_ids": [0], "sent2_word_ids": [3], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> rebels "}, {"sent1_word_ids": [0], "sent2_word_ids": [2], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> blames"}] |
[
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"Friday"
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[
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"less",
"is",
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"'",
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] | en | en | headlines | 7 | [{"sent1_word_ids": [0], "sent2_word_ids": [1, 2], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> In Kenya "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [4], "type": "SPE1", "score": 4.0, "comment": "Mall attackers <==> attackers "}, {"sent1_word_ids": [3], "sent2_word_ids": [5], "type": "EQUI", "score": 5.0, "comment": "used <==> used "}, {"sent1_word_ids": [4, 5, 6, 7, 8, 9], "sent2_word_ids": [6, 7, 8, 9, 10, 11], "type": "EQUI", "score": 5.0, "comment": "` less is more ' strategy <==> ` less is more ' strategy "}, {"sent1_word_ids": [0], "sent2_word_ids": [3], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> ,"}] |
[
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] | en | en | headlines | 8 | [{"sent1_word_ids": [0], "sent2_word_ids": [8], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> : "}, {"sent1_word_ids": [5, 6], "sent2_word_ids": [6, 7], "type": "EQUI", "score": 5.0, "comment": "Solomon Islands <==> Solomon Islands "}, {"sent1_word_ids": [3, 4], "sent2_word_ids": [4, 5], "type": "EQUI", "score": 5.0, "comment": "strikes off <==> strikes off "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [1, 2, 3], "type": "SIMI", "score": 4.0, "comment": "6.8 quake <==> Magnitude 6.3 quake "}, {"sent1_word_ids": [0], "sent2_word_ids": [9], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> USGS"}] |
[
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] | en | en | headlines | 9 | [{"sent1_word_ids": [4], "sent2_word_ids": [6], "type": "EQUI", "score": 5.0, "comment": "recognizes <==> recognize "}, {"sent1_word_ids": [0], "sent2_word_ids": [1], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> U.S. "}, {"sent1_word_ids": [2, 3], "sent2_word_ids": [4, 5], "type": "EQUI", "score": 5.0, "comment": "of Syria <==> of Syria "}, {"sent1_word_ids": [10, 11, 12], "sent2_word_ids": [0], "type": "NOALI", "score": null, "comment": "of Syrian people <==> -not aligned- "}, {"sent1_word_ids": [7, 8, 9], "sent2_word_ids": [8, 9, 10], "type": "SIMI", "score": 4.0, "comment": "as legitimate representative <==> as sole representative "}, {"sent1_word_ids": [1], "sent2_word_ids": [3], "type": "EQUI", "score": 5.0, "comment": "Friends <==> Friends "}, {"sent1_word_ids": [5, 6], "sent2_word_ids": [7], "type": "EQUI", "score": 5.0, "comment": "opposition coalition <==> opposition "}, {"sent1_word_ids": [0], "sent2_word_ids": [2], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> ,"}] |
[
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"sister",
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1,
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] | en | en | headlines | 10 | [{"sent1_word_ids": [2], "sent2_word_ids": [2], "type": "EQUI", "score": 5.0, "comment": "detained <==> detains "}, {"sent1_word_ids": [3, 4, 5, 6, 7, 8], "sent2_word_ids": [4, 5, 6, 7, 8, 9], "type": "EQUI", "score": 5.0, "comment": "for ` house sister ' scandal <==> for `` house sister '' scandal "}, {"sent1_word_ids": [1], "sent2_word_ids": [3], "type": "EQUI", "score": 5.0, "comment": "7 <==> 7 "}, {"sent1_word_ids": [0], "sent2_word_ids": [1], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> China"}] |
[
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";",
"stock",
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] | en | en | headlines | 11 | [{"sent1_word_ids": [8, 9, 10], "sent2_word_ids": [3], "type": "EQUI", "score": 5.0, "comment": "takes a beating <==> tumbles "}, {"sent1_word_ids": [1, 2, 3], "sent2_word_ids": [6, 7, 8], "type": "EQUI", "score": 5.0, "comment": "Boeing 787 Dreamliner <==> on 787 Dreamliner "}, {"sent1_word_ids": [4, 5], "sent2_word_ids": [4, 5], "type": "EQUI", "score": 5.0, "comment": "catches fire <==> after fire "}, {"sent1_word_ids": [7], "sent2_word_ids": [1, 2], "type": "EQUI", "score": 5.0, "comment": "stock <==> Boeing stock "}, {"sent1_word_ids": [6], "sent2_word_ids": [0], "type": "NOALI", "score": 0.0, "comment": "; <==> -not aligned-"}] |
[
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"Nigeria"
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0,
0,
0,
0,
0,
0
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0,
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] | en | en | headlines | 12 | [{"sent1_word_ids": [1], "sent2_word_ids": [0], "type": "NOALI", "score": 0.0, "comment": "Gunmen <==> -not aligned- "}, {"sent1_word_ids": [3, 4, 5], "sent2_word_ids": [1, 2, 3], "type": "EQUI", "score": 5.0, "comment": "seven foreign workers <==> Seven foreign workers "}, {"sent1_word_ids": [6, 7], "sent2_word_ids": [5, 6], "type": "EQUI", "score": 5.0, "comment": "in Nigeria <==> in Nigeria "}, {"sent1_word_ids": [2], "sent2_word_ids": [4], "type": "EQUI", "score": 5.0, "comment": "abduct <==> kidnapped"}] |
[
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"forces",
"in",
"West",
"Bank",
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"Jerusalem"
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] | en | en | headlines | 13 | [{"sent1_word_ids": [4, 5], "sent2_word_ids": [4, 5], "type": "EQUI", "score": 5.0, "comment": "Israeli forces <==> security forces "}, {"sent1_word_ids": [6, 7, 8, 9, 10], "sent2_word_ids": [6, 7, 8], "type": "EQUI", "score": 5.0, "comment": "in West Bank , Jerusalem <==> in W. Bank "}, {"sent1_word_ids": [2, 3], "sent2_word_ids": [2, 3], "type": "EQUI", "score": 5.0, "comment": "clash with <==> clash with "}, {"sent1_word_ids": [1], "sent2_word_ids": [1], "type": "EQUI", "score": 5.0, "comment": "Palestinians <==> Palestinians"}] |
[
"12",
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"in",
"bus",
"accident",
"in",
"Pakistan"
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"in",
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] | en | en | headlines | 14 | [{"sent1_word_ids": [3, 4, 5], "sent2_word_ids": [3, 4, 5], "type": "SPE1", "score": 4.0, "comment": "in bus accident <==> in road accident "}, {"sent1_word_ids": [2], "sent2_word_ids": [2], "type": "EQUI", "score": 5.0, "comment": "killed <==> killed "}, {"sent1_word_ids": [1], "sent2_word_ids": [1], "type": "SIMI", "score": 4.0, "comment": "12 <==> 10 "}, {"sent1_word_ids": [6, 7], "sent2_word_ids": [6, 7, 8], "type": "SPE2", "score": 4.0, "comment": "in Pakistan <==> in NW Pakistan"}] |
[
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"Family",
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"with",
"South"
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] | en | en | headlines | 15 | [{"sent1_word_ids": [3], "sent2_word_ids": [4], "type": "EQUI", "score": 5.0, "comment": "Postpones <==> postpones "}, {"sent1_word_ids": [0], "sent2_word_ids": [5], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> ' "}, {"sent1_word_ids": [4, 5], "sent2_word_ids": [6, 7], "type": "EQUI", "score": 5.0, "comment": "Family Reunions <==> family unions "}, {"sent1_word_ids": [6, 7], "sent2_word_ids": [8, 9, 10], "type": "EQUI", "score": 5.0, "comment": "with South <==> with South Korea "}, {"sent1_word_ids": [0], "sent2_word_ids": [3], "type": "NOALI", "score": 0.0, "comment": "-not aligned- <==> ` "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [1, 2], "type": "EQUI", "score": 5.0, "comment": "North Korea <==> North Korea"}] |
[
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"Beckham",
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"Retirement",
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"Soccer"
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"Beckham",
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] | [
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] | en | en | headlines | 16 | [{"sent1_word_ids": [5, 6], "sent2_word_ids": [4, 5], "type": "EQUI", "score": 5.0, "comment": "From Soccer <==> from football "}, {"sent1_word_ids": [3, 4], "sent2_word_ids": [3], "type": "EQUI_FACT", "score": 5.0, "comment": "Announces Retirement <==> retires "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [1, 2], "type": "EQUI", "score": 5.0, "comment": "David Beckham <==> David Beckham"}] |
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[
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[
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0.4,
0.4,
1,
1,
1,
1,
1,
1,
1,
1,
1
] | en | en | headlines | 99 | [{"sent1_word_ids": [0], "sent2_word_ids": [8, 9], "type": "NOALI", "score": null, "comment": "-not aligned- <==> in prison "}, {"sent1_word_ids": [0], "sent2_word_ids": [5, 6, 7], "type": "NOALI", "score": null, "comment": "-not aligned- <==> to 30 months "}, {"sent1_word_ids": [1, 2, 3], "sent2_word_ids": [1, 2, 3], "type": "SIMI", "score": 3.0, "comment": "Former LAPD officer <==> Former CIA officer "}, {"sent1_word_ids": [5, 6, 7], "sent2_word_ids": [0], "type": "NOALI", "score": null, "comment": "in Irvine slayings <==> -not aligned- "}, {"sent1_word_ids": [0], "sent2_word_ids": [4], "type": "NOALI", "score": null, "comment": "-not aligned- <==> sentenced "}, {"sent1_word_ids": [4], "sent2_word_ids": [0], "type": "NOALI", "score": null, "comment": "sought <==> -not aligned- "}, {"sent1_word_ids": [0], "sent2_word_ids": [10, 11, 12], "type": "NOALI", "score": null, "comment": "-not aligned- <==> for info leak"}] |
[
"Pakistan",
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"demands",
"`",
"blasphemy",
"'",
"rampage",
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"Pakistan-UN",
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"reveals",
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0.6,
0.6,
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1,
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1,
1,
1
] | en | en | headlines | 100 | [{"sent1_word_ids": [0], "sent2_word_ids": [4, 5], "type": "NOALI", "score": null, "comment": "-not aligned- <==> alarming levels "}, {"sent1_word_ids": [4, 5, 6, 7, 8], "sent2_word_ids": [0], "type": "NOALI", "score": null, "comment": "` blasphemy ' rampage answers <==> -not aligned- "}, {"sent1_word_ids": [1, 2], "sent2_word_ids": [1, 2], "type": "REL", "score": 2.0, "comment": "Pakistan court <==> Pakistan-UN report "}, {"sent1_word_ids": [0], "sent2_word_ids": [6, 7, 8], "type": "NOALI", "score": null, "comment": "-not aligned- <==> of drug use "}, {"sent1_word_ids": [0], "sent2_word_ids": [3], "type": "NOALI", "score": null, "comment": "-not aligned- <==> reveals "}, {"sent1_word_ids": [3], "sent2_word_ids": [0], "type": "NOALI", "score": null, "comment": "demands <==> -not aligned-"}] |
End of preview. Expand
in Dataset Viewer.
Training and test data for the task of Recognizing Semantic Differences (RSD).
See the paper for details on how the dataset was created, and see our code at https://github.com/ZurichNLP/recognizing-semantic-differences for an example of how to use the data for evaluation.
The data are derived from the SemEval-2016 Task 2 for Interpretable Semantic Textual Similarity organized by Agirre et al. (2016). The original URLs of the data are:
- Train: http://alt.qcri.org/semeval2016/task2/data/uploads/train_2015_10_22.utf-8.tar.gz
- Test: http://alt.qcri.org/semeval2016/task2/data/uploads/test_goldstandard.tar.gz
The translations into non-English languages have been created using machine translation (DeepL).
Citation
@inproceedings{vamvas-sennrich-2023-rsd,
title={Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents},
author={Jannis Vamvas and Rico Sennrich},
month = dec,
year = "2023",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
address = "Singapore",
publisher = "Association for Computational Linguistics",
}
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