Datasets › SPOT

SPOT (Sentiment Polarity Annotations Dataset)

Introduced by Stefanos Angelidis et al. in Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis27 Nov 2017 archive 2025-07-28

The SPOT dataset contains 197 reviews originating from the Yelp'13 and IMDB collections ([1][2]), annotated with segment-level polarity labels (positive/neutral/negative). Annotations have been gathered on 2 levels of granulatiry:

  • Sentences
  • Elementary Discourse Units (EDUs), i.e. sub-sentence clauses produced by a state-of-the-art RST parser

This dataset is intended to aid sentiment analysis research and, in particular, the evaluation of methods that attempt to predict sentiment on a fine-grained, segment-level basis.

Source: SPOT

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 3 papers for it but never published that list.

Dataset loaders archive 2025-07-28

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • SPOT

1 variant name, as the archive lists them.

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