Triple

T76196
Position Surface form Disambiguated ID Type / Status
Subject ET E1522 entity
Predicate usedInCity P4810 FINISHED
Object Miami E1524 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: Miami | Statement: [ET, usedInCity, Miami]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miami
Context triple: [ET, usedInCity, Miami]
  • A. Miami chosen
    Miami is a major coastal city in southeastern Florida known for its vibrant nightlife, diverse culture, and role as a global center for finance, tourism, and international trade.
  • B. Miami Beach
    Miami Beach is a coastal resort city in southeastern Florida known for its sandy beaches, Art Deco Historic District, and vibrant nightlife.
  • C. Miami metropolitan area
    The Miami metropolitan area is a major South Florida urban region centered on Miami, known for its large population, cultural diversity, international finance and trade, and status as a gateway to Latin America.
  • D. Orlando
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • E. 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.
  • 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_69a24c60d19c8190a1b6c105ca59ef5b completed Feb. 28, 2026, 2:01 a.m.
NER Named-entity recognition batch_69a2567c90308190a9b989c586f7e559 completed Feb. 28, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e43eaf88190b153139b9710d5d2 completed Feb. 28, 2026, 7:50 a.m.
Created at: Feb. 28, 2026, 2:06 a.m.