Triple

T21087234
Position Surface form Disambiguated ID Type / Status
Subject Texas Legends E519530 entity
Predicate city P40 FINISHED
Object Frisco 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: Frisco | Statement: [Texas Legends, city, Frisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frisco
Context triple: [Texas Legends, city, Frisco]
  • A. Frisco
    Frisco is the popular nickname for the historic St. Louis–San Francisco Railway, a major American railroad that operated across the Midwest and South.
  • B. Frisco, Texas chosen
    Frisco, Texas is a rapidly growing suburban city in the Dallas–Fort Worth metropolitan area known for its sports venues, retail centers, and family-friendly communities.
  • C. Grand Prairie
    Grand Prairie is a mid-sized suburban city in the Dallas–Fort Worth metropolitan area known for its family attractions, parks, and growing residential communities.
  • D. San Antonio
    San Antonio is a small locality within the municipality of Valfurva in the Lombardy region of northern Italy, situated in the Italian Alps.
  • E. San Antonio
    San Antonio is a barangay (village-level administrative division) within the municipality of Capul in the Philippines.
  • 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094be9388190b004fda23f301397 completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:50 p.m.