Triple

T10750765
Position Surface form Disambiguated ID Type / Status
Subject Syracuse Orange women's basketball E253565 entity
Predicate nickname P55 FINISHED
Object Orange E316023 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: Orange | Statement: [Syracuse Orange women's basketball, nickname, Orange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange
Context triple: [Syracuse Orange women's basketball, nickname, Orange]
  • A. Orange
    Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
  • B. Orange chosen
    Orange is the nickname and primary identity of Syracuse University's athletic teams, especially its prominent men's basketball program.
  • C. Orange
    Orange was the original name of the town now known as Hillsborough in North Carolina, reflecting its early colonial-era identity.
  • D. Orange
    Orange is a small town in north-central Massachusetts known for its rural character, historic mill village roots, and location along the Millers River.
  • E. Orange
    Orange is a common English surname of likely Norman or French origin, shared by various individuals including the British singer Jason Orange.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d71dc0ad188190b747bf9d10cf5de5 completed April 9, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69de23292f8c8190a52c94c03e7d476d completed April 14, 2026, 11:21 a.m.
Created at: April 8, 2026, 9:15 p.m.