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class StanfordSentimentTreeBankDatasetReader(DatasetReader):
 | def __init__(
 |     self,
 |     token_indexers: Dict[str, TokenIndexer] = None,
 |     tokenizer: Optional[Tokenizer] = None,
 |     use_subtrees: bool = False,
 |     granularity: str = "5-class",
 |     **kwargs
 | ) -> None

Reads tokens and their sentiment labels from the Stanford Sentiment Treebank.

The Stanford Sentiment Treebank comes with labels from 0 to 4. "5-class" uses these labels as is. "3-class" converts the problem into one of identifying whether a sentence is negative, positive, or neutral sentiment. In this case, 0 and 1 are grouped as label 0 (negative sentiment), 2 is converted to label 1 (neutral sentiment) and 3 and 4 are grouped as label 2 (positive sentiment). "2-class" turns it into a binary classification problem between positive and negative sentiment. 0 and 1 are grouped as the label 0 (negative sentiment), 2 (neutral) is discarded, and 3 and 4 are grouped as the label 1 (positive sentiment).

Expected format for each input line: a linearized tree, where nodes are labeled by their sentiment.

The output of read is a list of Instance s with the fields: tokens : TextField and label : LabelField

Registered as a DatasetReader with name "sst_tokens".


  • token_indexers : Dict[str, TokenIndexer], optional (default = {"tokens": SingleIdTokenIndexer()})
    We use this to define the input representation for the text. See TokenIndexer.
  • use_subtrees : bool, optional (default = False)
    Whether or not to use sentiment-tagged subtrees.
  • granularity : str, optional (default = "5-class")
    One of "5-class", "3-class", or "2-class", indicating the number of sentiment labels to use.


class StanfordSentimentTreeBankDatasetReader(DatasetReader):
 | ...
 | @overrides
 | def text_to_instance(
 |     self,
 |     tokens: List[str],
 |     sentiment: str = None
 | ) -> Optional[Instance]

We take pre-tokenized input here, because we might not have a tokenizer in this class.


  • tokens : List[str]
    The tokens in a given sentence.
  • sentiment : str, optional (default = None)
    The sentiment for this sentence.


  • An Instance containing the following fields:
    tokens : TextField The tokens in the sentence or phrase. label : LabelField The sentiment label of the sentence or phrase.