Triple

T18160418
Position Surface form Disambiguated ID Type / Status
Subject Lewiston, New York E434742 entity
Predicate hasRegionCode P3446 FINISHED
Object US-NY 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: US-NY | Statement: [Lewiston, New York, hasRegionCode, US-NY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-NY
Context triple: [Lewiston, New York, hasRegionCode, US-NY]
  • A. US-NY chosen
    US-NY is the region code for the U.S. state of New York.
  • B. NYSA
    NYSA is the commonly used abbreviation for the New York State Archives, the official repository for New York State government records and historical documents.
  • C. NY
    NY is the vehicle registration code used for cars registered in the Hungarian city of Nyíregyháza.
  • D. N.D.N.Y.
    N.D.N.Y. is the standard abbreviation for the United States District Court for the Northern District of New York, a federal trial court within the Second Circuit.
  • E. New York State
    New York State is a populous and economically significant state in the northeastern United States, known for its diverse landscapes, major cities like New York City, and central role in finance, culture, and politics.
  • 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dec21e6081909070491f679c873c completed April 19, 2026, 1:55 p.m.
Created at: April 10, 2026, 10:30 a.m.