Triple

T12692020
Position Surface form Disambiguated ID Type / Status
Subject Town of Utica E303228 entity
Predicate hasName P744 FINISHED
Object Utica E1097483 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: Utica | Statement: [Town of Utica, hasName, Utica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utica
Context triple: [Town of Utica, hasName, Utica]
  • A. Utica chosen
    Utica is a small town in Hinds County, Mississippi, known for its rural character and historic Southern setting.
  • B. Utica
    Utica was an ancient Phoenician colony in North Africa that became one of the earliest and most important urban centers in the western Mediterranean.
  • C. Útica
    Útica is a small Colombian town known for its warm climate and location in the Gualivá region of the Cundinamarca department.
  • D. Oneonta
    Oneonta is a small city in central Alabama that serves as the county seat and primary population center of Blount County.
  • E. Utica, New York
    Utica, New York is a small city in central New York State known historically as an industrial and transportation hub and today for its cultural diversity and role in the Mohawk Valley region.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961dbc91c8190bec50797bbd593db completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bab66488190a465e40f1181506e completed May 8, 2026, 3:42 a.m.
Created at: April 9, 2026, 5:22 p.m.