Triple

T23531915
Position Surface form Disambiguated ID Type / Status
Subject Shawangunk E576591 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: [Shawangunk, hasRegionCode, US-NY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-NY
Context triple: [Shawangunk, 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used abbreviation for the New York State Archives, the official repository for New York State government records and historical documents.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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ac78581c8190bd9d09ce2be8029d completed April 29, 2026, 7 a.m.
Created at: April 17, 2026, 6:09 p.m.