Triple

T194695
Position Surface form Disambiguated ID Type / Status
Subject Super Bowl XXXIX E3793 entity
Predicate city P40 FINISHED
Object Jacksonville E20727 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: Jacksonville | Statement: [Super Bowl XXXIX, city, Jacksonville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jacksonville
Context triple: [Super Bowl XXXIX, city, Jacksonville]
  • A. Jacksonville, Florida chosen
    Jacksonville, Florida is a major city in northeastern Florida known for its extensive riverfront, large land area, and role as a regional economic and transportation hub.
  • B. Orlando
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • C. Jacksonville metropolitan area
    The Jacksonville metropolitan area is a Northeast Florida urban region centered on the city of Jacksonville, encompassing surrounding communities and suburbs along the Atlantic coast and St. Johns River.
  • D. Tampa, Florida
    Tampa, Florida is a major city on Florida’s Gulf Coast known for its professional sports teams, port and business center, and role as a key hub in the greater Tampa Bay area.
  • E. Tallahassee
    Tallahassee is a city in the Florida Panhandle known for its government institutions, universities, and rolling, forested hills.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a25969425081908e178db8ba4631c2 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3672e822c8190be0d6c0714034ff7 completed Feb. 28, 2026, 10:07 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.