Triple

T13504377
Position Surface form Disambiguated ID Type / Status
Subject Kissimmee station E320974 entity
Predicate regionServed P82 FINISHED
Object Greater Orlando E156309 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: Greater Orlando | Statement: [Kissimmee station, regionServed, Greater Orlando]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater Orlando
Context triple: [Kissimmee station, regionServed, Greater Orlando]
  • A. Orlando–Kissimmee–Sanford metropolitan area chosen
    The Orlando–Kissimmee–Sanford metropolitan area is a major Central Florida urban region centered on Orlando, known for its tourism industry, theme parks, and rapidly growing population.
  • B. Orlando
    Orlando is a common Italian surname borne by numerous individuals, including notable political and cultural figures.
  • C. 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."
  • D. Orlando
    Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
  • E. 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.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf810e248190a060481004503f96 completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba835f08190bdc21de864e0fcc8 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:43 p.m.