Datasets:

jmichaelov
/

lm_syneval

We present a dataset for evaluating the grammaticality of the predictions of a language model. We automatically construct a large number of minimally different pairs of English sentences, each consisting of a grammatical and an ungrammatical sentence. The sentence pairs represent different variations of structure-sensitive phenomena: subject-verb agreement, reflexive anaphora and negative polarity items. We expect a language model to assign a higher probability to the grammatical sentence than the ungrammatical one.

(Marvin and Linzen, 2018)

Dataset Details

Dataset Description

Curated by: Rebecca Marvin and Tal Linzen
Language(s) (NLP): English
License: MIT License

Dataset Sources

Repository: https://github.com/BeckyMarvin/LM_syneval
Paper: Targeted Syntactic Evaluation of Language Models

Uses

Assessing the grammatical capabilities of language models trained on English.

Direct Use

Assessing the grammatical capabilities of language models trained on English with a focus on subject-verb agreement, reflexive anaphora, and negative polarity items.

Out-of-Scope Use

This dataset is only relevant for studying language models trained on English. The grammatical rules evaluated by this dataset may not be valid for some varieties of English.

Dataset Structure

lm_syneval
- lm_syneval__reflexives
  - lm_syneval__reflexives__simple_reflexives
    - lm_syneval__reflexives__simple_reflexives__sing_MS_ANPHR
    - lm_syneval__reflexives__simple_reflexives__plur_MS_ANPHR
  - lm_syneval__reflexives__reflexive_sent_comp
    - lm_syneval__reflexives__reflexive_sent_comp__sing_MS_ANPHR_sing_BS
    - lm_syneval__reflexives__reflexive_sent_comp__sing_MS_ANPHR_plur_BS
    - lm_syneval__reflexives__reflexive_sent_comp__plur_MS_ANPHR_sing_BS
    - lm_syneval__reflexives__reflexive_sent_comp__plur_MS_ANPHR_plur_BS
  - lm_syneval__reflexives__reflexives_across
    - lm_syneval__reflexives__reflexives_across__sing_MS_ANPHR_sing_ES_EV
    - lm_syneval__reflexives__reflexives_across__sing_MS_ANPHR_plur_ES_EV
    - lm_syneval__reflexives__reflexives_across__plur_MS_ANPHR_sing_ES_EV
    - lm_syneval__reflexives__reflexives_across__plur_MS_ANPHR_plur_ES_EV
- lm_syneval__agreement
  - lm_syneval__agreement__obj_rel_within_inanim
    - lm_syneval__agreement__obj_rel_within_inanim__sing_ES_EV_sing_IS_IV
    - lm_syneval__agreement__obj_rel_within_inanim__sing_ES_EV_plur_IS_IV
    - lm_syneval__agreement__obj_rel_within_inanim__plur_ES_EV_sing_IS_IV
    - lm_syneval__agreement__obj_rel_within_inanim__plur_ES_EV_plur_IS_IV
  - lm_syneval__agreement__vp_coord
    - lm_syneval__agreement__vp_coord__sing_MS_MV_MV
    - lm_syneval__agreement__vp_coord__plur_MS_MV_MV
  - lm_syneval__agreement__sent_comp
    - lm_syneval__agreement__sent_comp__sing_MS_MV_sing_BS
    - lm_syneval__agreement__sent_comp__sing_MS_MV_plur_BS
    - lm_syneval__agreement__sent_comp__plur_MS_MV_sing_BS
    - lm_syneval__agreement__sent_comp__plur_MS_MV_plur_BS
  - lm_syneval__agreement__obj_rel_no_comp_within_inanim
    - lm_syneval__agreement__obj_rel_no_comp_within_inanim__sing_ES_EV_sing_IS_IV
    - lm_syneval__agreement__obj_rel_no_comp_within_inanim__sing_ES_EV_plur_IS_IV
    - lm_syneval__agreement__obj_rel_no_comp_within_inanim__plur_ES_EV_sing_IS_IV
    - lm_syneval__agreement__obj_rel_no_comp_within_inanim__plur_ES_EV_plur_IS_IV
  - lm_syneval__agreement__obj_rel_within_anim
    - lm_syneval__agreement__obj_rel_within_anim__sing_ES_EV_sing_MS_MV
    - lm_syneval__agreement__obj_rel_within_anim__sing_ES_EV_plur_MS_MV
    - lm_syneval__agreement__obj_rel_within_anim__plur_ES_EV_sing_MS_MV
    - lm_syneval__agreement__obj_rel_within_anim__plur_ES_EV_plur_MS_MV
  - lm_syneval__agreement__subj_rel
    - lm_syneval__agreement__subj_rel__sing_MS_EV_MV_sing_ES
    - lm_syneval__agreement__subj_rel__sing_MS_EV_MV_plur_ES
    - lm_syneval__agreement__subj_rel__plur_MS_EV_MV_sing_ES
    - lm_syneval__agreement__subj_rel__plur_MS_EV_MV_plur_ES
  - lm_syneval__agreement__prep_inanim
    - lm_syneval__agreement__prep_inanim__sing_IS_IV_sing_ES
    - lm_syneval__agreement__prep_inanim__sing_IS_IV_plur_ES
    - lm_syneval__agreement__prep_inanim__plur_IS_IV_sing_ES
    - lm_syneval__agreement__prep_inanim__plur_IS_IV_plur_ES
  - lm_syneval__agreement__long_vp_coord
    - lm_syneval__agreement__long_vp_coord__sing_MS_LMV_LMV
    - lm_syneval__agreement__long_vp_coord__plur_MS_LMV_LMV
  - lm_syneval__agreement__obj_rel_across_anim
    - lm_syneval__agreement__obj_rel_across_anim__sing_MS_MV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_across_anim__sing_MS_MV_plur_ES_EV
    - lm_syneval__agreement__obj_rel_across_anim__plur_MS_MV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_across_anim__plur_MS_MV_plur_ES_EV
  - lm_syneval__agreement__obj_rel_across_inanim
    - lm_syneval__agreement__obj_rel_across_inanim__sing_IS_IV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_across_inanim__sing_IS_IV_plur_ES_EV
    - lm_syneval__agreement__obj_rel_across_inanim__plur_IS_IV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_across_inanim__plur_IS_IV_plur_ES_EV
  - lm_syneval__agreement__obj_rel_no_comp_across_anim
    - lm_syneval__agreement__obj_rel_no_comp_across_anim__sing_MS_MV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_anim__sing_MS_MV_plur_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_anim__plur_MS_MV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_anim__plur_MS_MV_plur_ES_EV
  - lm_syneval__agreement__obj_rel_no_comp_across_inanim
    - lm_syneval__agreement__obj_rel_no_comp_across_inanim__sing_IS_IV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_inanim__sing_IS_IV_plur_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_inanim__plur_IS_IV_sing_ES_EV
    - lm_syneval__agreement__obj_rel_no_comp_across_inanim__plur_IS_IV_plur_ES_EV
  - lm_syneval__agreement__simple_agrmt
    - lm_syneval__agreement__simple_agrmt__sing_MS_MV
    - lm_syneval__agreement__simple_agrmt__plur_MS_MV
  - lm_syneval__agreement__prep_anim
    - lm_syneval__agreement__prep_anim__sing_MS_MV_sing_ES
    - lm_syneval__agreement__prep_anim__sing_MS_MV_plur_ES
    - lm_syneval__agreement__prep_anim__plur_MS_MV_sing_ES
    - lm_syneval__agreement__prep_anim__plur_MS_MV_plur_ES
  - lm_syneval__agreement__obj_rel_no_comp_within_anim
    - lm_syneval__agreement__obj_rel_no_comp_within_anim__sing_ES_EV_sing_MS_MV
    - lm_syneval__agreement__obj_rel_no_comp_within_anim__sing_ES_EV_plur_MS_MV
    - lm_syneval__agreement__obj_rel_no_comp_within_anim__plur_ES_EV_sing_MS_MV
    - lm_syneval__agreement__obj_rel_no_comp_within_anim__plur_ES_EV_plur_MS_MV
- lm_syneval__npi
  - lm_syneval__npi__npi_across_anim
    - lm_syneval__npi__npi_across_anim__past
    - lm_syneval__npi__npi_across_anim__future
  - lm_syneval__npi__npi_across_inanim
    - lm_syneval__npi__npi_across_inanim__past
    - lm_syneval__npi__npi_across_inanim__future
  - lm_syneval__npi__simple_npi_anim
    - lm_syneval__npi__simple_npi_anim__past
    - lm_syneval__npi__simple_npi_anim__future
  - lm_syneval__npi__simple_npi_inanim
    - lm_syneval__npi__simple_npi_inanim__past
    - lm_syneval__npi__simple_npi_inanim__future

Dataset Creation

Curation Rationale

To assess the grammatical capabilities of language models trained on English.

Source Data

Automatically generated based on a template.

Data Collection and Processing

See above.

Who are the source data producers?

Rebecca Marvin and Tal Linzen

Annotation process

N/A

Who are the annotators?

N/A

Personal and Sensitive Information

N/A

Bias, Risks, and Limitations

The dataset is based on on standard varieties of English, and only covers a limited number of syntactic phenomena.

Recommendations

This dataset should not be considered sufficient to assess the full English-language grammatical capabilities of a language model.

Citation

BibTeX:

@inproceedings{marvin-linzen-2018-targeted,
    title = "Targeted Syntactic Evaluation of Language Models",
    author = "Marvin, Rebecca  and
      Linzen, Tal",
    editor = "Riloff, Ellen  and
      Chiang, David  and
      Hockenmaier, Julia  and
      Tsujii, Jun{'}ichi",
    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
    month = oct # "-" # nov,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/D18-1151/",
    doi = "10.18653/v1/D18-1151",
    pages = "1192--1202",
    abstract = "We present a data set for evaluating the grammaticality of the predictions of a language model. We automatically construct a large number of minimally different pairs of English sentences, each consisting of a grammatical and an ungrammatical sentence. The sentence pairs represent different variations of structure-sensitive phenomena: subject-verb agreement, reflexive anaphora and negative polarity items. We expect a language model to assign a higher probability to the grammatical sentence than the ungrammatical one. In an experiment using this data set, an LSTM language model performed poorly on many of the constructions. Multi-task training with a syntactic objective (CCG supertagging) improved the LSTM`s accuracy, but a large gap remained between its performance and the accuracy of human participants recruited online. This suggests that there is considerable room for improvement over LSTMs in capturing syntax in a language model."
}

APA:

Marvin, R., & Linzen, T. (2018). Targeted Syntactic Evaluation of Language Models. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (pp. 1192-1202).

Downloads last month: 61

Size of downloaded dataset files:

15.4 MB

Size of the auto-converted Parquet files:

3.67 MB

Number of rows:

158,084

itemID int64 0 199	sentence_good stringlengths 71 95	sentence_bad stringlengths 70 96
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1	The authors know many different foreign languages and are twenty three years old.	The authors know many different foreign languages and is twenty three years old.
2	The authors know many different foreign languages and enjoy playing tennis with colleagues.	The authors know many different foreign languages and enjoys playing tennis with colleagues.
3	The authors know many different foreign languages and write in a journal every day.	The authors know many different foreign languages and writes in a journal every day.
4	The authors like to watch television shows and know many different foreign languages.	The authors like to watch television shows and knows many different foreign languages.
5	The authors like to watch television shows and are twenty three years old.	The authors like to watch television shows and is twenty three years old.
6	The authors like to watch television shows and enjoy playing tennis with colleagues.	The authors like to watch television shows and enjoys playing tennis with colleagues.
7	The authors like to watch television shows and write in a journal every day.	The authors like to watch television shows and writes in a journal every day.
8	The authors are twenty three years old and know many different foreign languages.	The authors are twenty three years old and knows many different foreign languages.
9	The authors are twenty three years old and like to watch television shows.	The authors are twenty three years old and likes to watch television shows.
10	The authors are twenty three years old and enjoy playing tennis with colleagues.	The authors are twenty three years old and enjoys playing tennis with colleagues.
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14	The authors enjoy playing tennis with colleagues and are twenty three years old.	The authors enjoy playing tennis with colleagues and is twenty three years old.
15	The authors enjoy playing tennis with colleagues and write in a journal every day.	The authors enjoy playing tennis with colleagues and writes in a journal every day.
16	The authors write in a journal every day and know many different foreign languages.	The authors write in a journal every day and knows many different foreign languages.
17	The authors write in a journal every day and like to watch television shows.	The authors write in a journal every day and likes to watch television shows.
18	The authors write in a journal every day and are twenty three years old.	The authors write in a journal every day and is twenty three years old.
19	The authors write in a journal every day and enjoy playing tennis with colleagues.	The authors write in a journal every day and enjoys playing tennis with colleagues.
20	The pilots know many different foreign languages and like to watch television shows.	The pilots know many different foreign languages and likes to watch television shows.
21	The pilots know many different foreign languages and are twenty three years old.	The pilots know many different foreign languages and is twenty three years old.
22	The pilots know many different foreign languages and enjoy playing tennis with colleagues.	The pilots know many different foreign languages and enjoys playing tennis with colleagues.
23	The pilots know many different foreign languages and write in a journal every day.	The pilots know many different foreign languages and writes in a journal every day.
24	The pilots like to watch television shows and know many different foreign languages.	The pilots like to watch television shows and knows many different foreign languages.
25	The pilots like to watch television shows and are twenty three years old.	The pilots like to watch television shows and is twenty three years old.
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29	The pilots are twenty three years old and like to watch television shows.	The pilots are twenty three years old and likes to watch television shows.
30	The pilots are twenty three years old and enjoy playing tennis with colleagues.	The pilots are twenty three years old and enjoys playing tennis with colleagues.
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37	The pilots write in a journal every day and like to watch television shows.	The pilots write in a journal every day and likes to watch television shows.
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39	The pilots write in a journal every day and enjoy playing tennis with colleagues.	The pilots write in a journal every day and enjoys playing tennis with colleagues.
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46	The surgeons like to watch television shows and enjoy playing tennis with colleagues.	The surgeons like to watch television shows and enjoys playing tennis with colleagues.
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48	The surgeons are twenty three years old and know many different foreign languages.	The surgeons are twenty three years old and knows many different foreign languages.
49	The surgeons are twenty three years old and like to watch television shows.	The surgeons are twenty three years old and likes to watch television shows.
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53	The surgeons enjoy playing tennis with colleagues and like to watch television shows.	The surgeons enjoy playing tennis with colleagues and likes to watch television shows.
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55	The surgeons enjoy playing tennis with colleagues and write in a journal every day.	The surgeons enjoy playing tennis with colleagues and writes in a journal every day.
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57	The surgeons write in a journal every day and like to watch television shows.	The surgeons write in a journal every day and likes to watch television shows.
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59	The surgeons write in a journal every day and enjoy playing tennis with colleagues.	The surgeons write in a journal every day and enjoys playing tennis with colleagues.
60	The farmers know many different foreign languages and like to watch television shows.	The farmers know many different foreign languages and likes to watch television shows.
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62	The farmers know many different foreign languages and enjoy playing tennis with colleagues.	The farmers know many different foreign languages and enjoys playing tennis with colleagues.
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76	The farmers write in a journal every day and know many different foreign languages.	The farmers write in a journal every day and knows many different foreign languages.
77	The farmers write in a journal every day and like to watch television shows.	The farmers write in a journal every day and likes to watch television shows.
78	The farmers write in a journal every day and are twenty three years old.	The farmers write in a journal every day and is twenty three years old.
79	The farmers write in a journal every day and enjoy playing tennis with colleagues.	The farmers write in a journal every day and enjoys playing tennis with colleagues.
80	The managers know many different foreign languages and like to watch television shows.	The managers know many different foreign languages and likes to watch television shows.
81	The managers know many different foreign languages and are twenty three years old.	The managers know many different foreign languages and is twenty three years old.
82	The managers know many different foreign languages and enjoy playing tennis with colleagues.	The managers know many different foreign languages and enjoys playing tennis with colleagues.
83	The managers know many different foreign languages and write in a journal every day.	The managers know many different foreign languages and writes in a journal every day.
84	The managers like to watch television shows and know many different foreign languages.	The managers like to watch television shows and knows many different foreign languages.
85	The managers like to watch television shows and are twenty three years old.	The managers like to watch television shows and is twenty three years old.
86	The managers like to watch television shows and enjoy playing tennis with colleagues.	The managers like to watch television shows and enjoys playing tennis with colleagues.
87	The managers like to watch television shows and write in a journal every day.	The managers like to watch television shows and writes in a journal every day.
88	The managers are twenty three years old and know many different foreign languages.	The managers are twenty three years old and knows many different foreign languages.
89	The managers are twenty three years old and like to watch television shows.	The managers are twenty three years old and likes to watch television shows.
90	The managers are twenty three years old and enjoy playing tennis with colleagues.	The managers are twenty three years old and enjoys playing tennis with colleagues.
91	The managers are twenty three years old and write in a journal every day.	The managers are twenty three years old and writes in a journal every day.
92	The managers enjoy playing tennis with colleagues and know many different foreign languages.	The managers enjoy playing tennis with colleagues and knows many different foreign languages.
93	The managers enjoy playing tennis with colleagues and like to watch television shows.	The managers enjoy playing tennis with colleagues and likes to watch television shows.
94	The managers enjoy playing tennis with colleagues and are twenty three years old.	The managers enjoy playing tennis with colleagues and is twenty three years old.
95	The managers enjoy playing tennis with colleagues and write in a journal every day.	The managers enjoy playing tennis with colleagues and writes in a journal every day.
96	The managers write in a journal every day and know many different foreign languages.	The managers write in a journal every day and knows many different foreign languages.
97	The managers write in a journal every day and like to watch television shows.	The managers write in a journal every day and likes to watch television shows.
98	The managers write in a journal every day and are twenty three years old.	The managers write in a journal every day and is twenty three years old.
99	The managers write in a journal every day and enjoy playing tennis with colleagues.	The managers write in a journal every day and enjoys playing tennis with colleagues.