Triple

T1200395
Position Surface form Disambiguated ID Type / Status
Subject The Golden Girls E25767 entity
Predicate setInState P8707 FINISHED
Object Florida E549 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: Florida | Statement: [The Golden Girls, setInState, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florida
Context triple: [The Golden Girls, setInState, Florida]
  • A. Florida chosen
    Florida is a southeastern U.S. state known for its warm climate, extensive beaches, tourism industry centered on attractions like Walt Disney World, and significant cultural and economic influence.
  • B. Florida
    Florida is a small rural town located in the northern part of Berkshire County, Massachusetts, known for its mountainous terrain and proximity to the Mohawk Trail.
  • C. Esto, Florida
    Esto, Florida is a small rural town located in Holmes County in the Florida Panhandle near the Alabama state line.
  • D. Louisiana
    Louisiana is a U.S. state in the Deep South known for its unique Creole and Cajun cultures, the city of New Orleans, and its rich musical and culinary traditions.
  • E. Georgia
    Georgia is a country at the crossroads of Eastern Europe and Western Asia, known for its ancient culture, mountainous landscapes, and historic role along the Silk Road.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9ec3488190afe35af54efae5e9 completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac763827b08190b84cc18a5cfa64fc completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:46 p.m.