Triple

T2906375
Position Surface form Disambiguated ID Type / Status
Subject Orlando City SC E62773 entity
Predicate stadiumLocation P40 FINISHED
Object Orlando, Florida E11265 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: [Orlando City SC, stadiumLocation, Orlando, Florida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlando, Florida
Context triple: [Orlando City SC, stadiumLocation, 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 a historic township area within Soweto, South Africa, known for its central role in the anti-apartheid struggle and vibrant local culture.
  • D. Kissimmee, Florida
    Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
  • E. Jacksonville, Florida
    Jacksonville, Florida is a major city in northeastern Florida known for its extensive riverfront, large land area, and role as a regional economic and transportation hub.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0cee7988190875665145c3cd605 completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2358bd4cc81908970e1d3cdc95b5d completed March 12, 2026, 3:39 a.m.
Created at: March 6, 2026, 10:11 p.m.