Triple

T15284466
Position Surface form Disambiguated ID Type / Status
Subject Beauvoir E365358 entity
Predicate city P40 FINISHED
Object Biloxi E74285 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: Biloxi | Statement: [Beauvoir, city, Biloxi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biloxi
Context triple: [Beauvoir, city, Biloxi]
  • A. Biloxi chosen
    Biloxi is a coastal Mississippi city known for its beaches, casinos, and seafood industry along the Gulf of Mexico.
  • B. Pascagoula
    Pascagoula is a coastal city in southeastern Mississippi known for its major shipbuilding industry and location along the Gulf of Mexico.
  • C. Gulfport–Biloxi metropolitan area
    The Gulfport–Biloxi metropolitan area is a coastal urban region in southern Mississippi centered on the cities of Gulfport and Biloxi, known for its tourism, casinos, and Gulf Coast beaches.
  • D. Gulfport, Mississippi
    Gulfport, Mississippi is a coastal city on the Gulf of Mexico known for its port, beaches, and role as a major urban center in southern Mississippi.
  • E. Moss Point
    Moss Point is a small coastal city in Jackson County, Mississippi, known for its location along the Pascagoula River and proximity to the Gulf Coast.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00e53c9588190a6cb61ac8805c706 completed April 15, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff4542d4308190bebf13dff1ebfe08 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 3:15 a.m.