Triple

T15446082
Position Surface form Disambiguated ID Type / Status
Subject University of Louisiana at Lafayette E370025 entity
Predicate mascot P52 FINISHED
Object Cayenne E161877 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: Cayenne | Statement: [University of Louisiana at Lafayette, mascot, Cayenne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cayenne
Context triple: [University of Louisiana at Lafayette, mascot, Cayenne]
  • A. Cayenne chosen
    Cayenne is the principal city and administrative center of French Guiana, located on the Atlantic coast in northeastern South America.
  • B. Naiche
    Naiche was the last hereditary chief of the Chiricahua Apache and a prominent leader during the final phase of the Apache resistance against the United States.
  • C. Darien
    Darien is a character in the Disney Channel series "K.C. Undercover" who serves as a romantic interest for the teenage spy K.C. Cooper.
  • D. Darien
    Darien is a coastal town in Fairfield County, Connecticut, known for its affluent residential character and location along Long Island Sound.
  • E. Ventanarosa
    Ventanarosa is a film and television production company founded by Salma Hayek, known for producing culturally rich, often Latinx-focused projects.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21adb6b88190b573068bda223892 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:21 a.m.