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{"seq":["A soviet assertions is a assertions","A soviet assertions is a declaration","A soviet asser(...TRUNCATED)
{"seq":["A weekly load is a load","A weekly load is a weight","A weekly load is a weekly weight","A (...TRUNCATED)
{"seq":["A polish rifle is a rifle","A polish rifle is a firearm","A polish rifle is a polish firear(...TRUNCATED)
{"seq":["A mexican dealer is a dealer","A mexican dealer is a merchant","A mexican dealer is a mexic(...TRUNCATED)
{"seq":["A irish mac is a mac","A irish mac is a raincoat","A irish mac is a irish raincoat","A basi(...TRUNCATED)
{"seq":["A digital status is a status","A digital status is a state","A digital status is a digital (...TRUNCATED)
{"seq":["A private speakers is a speakers","A private speakers is a articulator","A private speakers(...TRUNCATED)
{"seq":["A democratic security is a security","A democratic security is a safety","A democratic secu(...TRUNCATED)
{"seq":["A chinese representatives is a representatives","A chinese representatives is a negotiator"(...TRUNCATED)
{"seq":["A dead path is a path","A dead path is a course","A dead path is a dead course","A clinical(...TRUNCATED)

PLANE Out-of-Distribution Sets

PLANE (phrase-level adjective-noun entailment) is a benchmark to test models on fine-grained compositional inference. The current dataset contains five sampled splits, used in the supervised experiments of Bertolini et al., 22.

Data Structure

The dataset is organised around five Train/test_split#, each containing a training and test set of circa 60K and 2K.


Each entrance has 6 features: seq, label, Adj_Class, Adj, Nn, Hy

  • seq:test sequense
  • label: ground truth (1:entialment, 0:no-entailment)
  • Adj_Class: the class of the sequence adjectives
  • Adj: the adjective of the sequence (I: intersective, S: subsective, O: intensional)
  • Nn: the noun
  • Hy: the noun's hypericum

Each sample in seq can take one of three forms (or inference types, in paper):

  • An Adjective-Noun is a Noun (e.g. A red car is a car)
  • An Adjective-Noun is a Hypernym(Noun) (e.g. A red car is a vehicle)
  • An Adjective-Noun is a Adjective-Hypernym(Noun) (e.g. A red car is a red vehicle)

Please note that, as specified in the paper, the ground truth is automatically assigned based on the linguistic rule that governs the interaction between each adjective class and inference type – see the paper for more detail.

Trained Model

You can find a tuned BERT-base model (tuned and validated using the 2nd split) here.


If you use PLANE for your work, please cite the main COLING 2022 paper.

    title = "Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment",
    author = "Bertolini, Lorenzo  and
      Weeds, Julie  and
      Weir, David",
    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "International Committee on Computational Linguistics",
    url = "",
    pages = "4084--4100",
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Models trained or fine-tuned on lorenzoscottb/PLANE-ood