Triple

T19341027
Position Surface form Disambiguated ID Type / Status
Subject First Niagara Center E483754 entity
Predicate hasCity P316 FINISHED
Object Buffalo 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: Buffalo | Statement: [First Niagara Center, hasCity, Buffalo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buffalo
Context triple: [First Niagara Center, hasCity, Buffalo]
  • A. Buffalo chosen
    Buffalo is a major city in western New York State known for its industrial history, proximity to Niagara Falls, and namesake Buffalo-style chicken wings.
  • B. Rochester
    Rochester is a historic cathedral city and former market town in Kent, England, known for its Norman castle, Romanesque cathedral, and strong associations with the novelist Charles Dickens.
  • C. Rochester
    Rochester is a small village located in Lorain County in the U.S. state of Ohio.
  • D. Rochester
    Rochester is a small city in northern Indiana that serves as the administrative and commercial hub of Fulton County.
  • E. Rochester
    Rochester is a rural town in northern Victoria, Australia, known for its agricultural community and location near the Campaspe River.
  • 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61856c0948190a3166b3bf3810e43 completed April 20, 2026, 12:13 p.m.
Created at: April 10, 2026, 1:33 p.m.