Triple

T18629028
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin School for the Deaf E455360 entity
Predicate languageOfInstruction P56 FINISHED
Object American Sign Language NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: American Sign Language | Statement: [Wisconsin School for the Deaf, languageOfInstruction, American Sign Language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: American Sign Language
Context triple: [Wisconsin School for the Deaf, languageOfInstruction, American Sign Language]
  • A. American Sign Language chosen
    American Sign Language is a natural visual-gestural language used primarily by Deaf communities in the United States and parts of Canada, with its own distinct grammar and vocabulary separate from spoken English.
  • B. ASL
    ASL is the ICAO airline designator used to identify Air Serbia in international aviation operations and communications.
  • C. ASL
    ASL is the three-letter station code used to identify Arsenal Underground station on the London Underground network.
  • D. ASL
    ASL is an international scholarly organization devoted to the advancement of research and education in symbolic logic and its applications.
  • E. ASL
    ASL is a German vehicle registration code used for cars registered in the Salzlandkreis district of Saxony-Anhalt.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54f06f4a081909b64f33814577488 completed April 19, 2026, 9:54 p.m.
Created at: April 10, 2026, 11:46 a.m.