Triple

T20163984
Position Surface form Disambiguated ID Type / Status
Subject The Funtastic World of Hanna-Barbera E491782 entity
Predicate locatedIn P40 FINISHED
Object Orlando, Florida NE NERFINISHED

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: [The Funtastic World of Hanna-Barbera, locatedIn, Orlando, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlando, Florida
Context triple: [The Funtastic World of Hanna-Barbera, locatedIn, Orlando, Florida]
  • A. Orlando chosen
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • B. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • C. Orlando
    Orlando is the young, virtuous, and romantically idealistic hero of Shakespeare’s comedy "As You Like It," known for his love for Rosalind and his conflict with his elder brother.
  • D. Orlando
    Orlando is the Italian literary counterpart of the medieval knight Roland, best known as the chivalric hero of epic poems such as "Orlando Furioso."
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66841b7d88190af3606f762d87b24 completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.