Triple

T1662682
Position Surface form Disambiguated ID Type / Status
Subject Halesite, New York E35943 entity
Predicate bordersWaterBody P212 FINISHED
Object Huntington Harbor E20528 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: Huntington Harbor | Statement: [Halesite, New York, bordersWaterBody, Huntington Harbor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huntington Harbor
Context triple: [Halesite, New York, bordersWaterBody, Huntington Harbor]
  • A. Huntington Harbor chosen
    Huntington Harbor is a sheltered waterfront area and marina district on Long Island’s north shore, known for recreational boating and scenic coastal views.
  • B. Calumet Harbor
    Calumet Harbor is a commercial and industrial harbor on the southwest shore of Lake Michigan that serves as a key shipping and transportation hub for the Chicago region.
  • C. Montrose Harbor
    Montrose Harbor is a popular Chicago marina on Lake Michigan known for its boating facilities, skyline views, and proximity to Montrose Beach and parkland.
  • D. Belmar
    Belmar is a popular coastal borough in Monmouth County, New Jersey, known for its sandy beaches, boardwalk, and vibrant summer tourism scene.
  • E. Belmar
    Belmar is a prominent mixed-use shopping, dining, and entertainment district serving as a central urban hub in Lakewood, Colorado.
  • 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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90ab5d1a08190a3325ff203b573fb completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad71adb0388190b358e83fa8dfaef5 completed March 8, 2026, 12:55 p.m.
Created at: March 4, 2026, 7:29 p.m.