Triple

T5072292
Position Surface form Disambiguated ID Type / Status
Subject Universal Parks & Resorts E114308 entity
Predicate headquartersLocation P62 FINISHED
Object Orlando, Florida E472337 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: Orlando, Florida | Statement: [Universal Parks & Resorts, headquartersLocation, Orlando, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlando, Florida
Context triple: [Universal Parks & Resorts, headquartersLocation, Orlando, Florida]
  • A. Orlando
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • C. Orlando
    Orlando is a 1992 British period fantasy film, based on Virginia Woolf’s novel, in which Tilda Swinton plays an androgynous noble who lives for centuries while changing gender.
  • D. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • E. Orlando, Florida, United States chosen
    Orlando, Florida, United States is a major Central Florida city known for its world-famous theme parks, tourism industry, and role as a hub for entertainment and pop music.
  • 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_69bd443cf28c8190ad371d603563dbdd completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74ce140881909a2874663244c0db completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb1110a388190a5db1c94b3d60d6b completed March 21, 2026, 2:54 p.m.
Created at: March 20, 2026, 1:39 p.m.