Triple

T6215791
Position Surface form Disambiguated ID Type / Status
Subject University of San Francisco women’s basketball team E138983 entity
Predicate mascot P52 FINISHED
Object Don E75078 NE FINISHED

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: Don | Statement: [University of San Francisco women’s basketball team, mascot, Don]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don
Context triple: [University of San Francisco women’s basketball team, mascot, Don]
  • A. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • B. Don chosen
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • C. Danny
    Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
  • D. Danny
    Danny is a masculine given name, often used as a diminutive of Daniel.
  • E. Danny
    Danny is the young, psychically gifted son of Jack Torrance in Stephen King’s horror novel "The Shining" and its film adaptations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a0e0488190b71b42386bacf982 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dacf1788190a655c39bd248fde8 completed March 24, 2026, 4:06 a.m.
Created at: March 22, 2026, 4:21 p.m.