Triple

T12279038
Position Surface form Disambiguated ID Type / Status
Subject Johnshaven E292666 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Montrose E27714 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: Montrose | Statement: [Johnshaven, hasNearbySettlement, Montrose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montrose
Context triple: [Johnshaven, hasNearbySettlement, Montrose]
  • A. Montrose
    Montrose is a residential neighborhood within the town of Wakefield in Middlesex County, Massachusetts.
  • B. Montrose chosen
    Montrose is a coastal town in eastern Scotland known for its historic harbor, sandy beach, and surrounding nature reserves.
  • C. Montrose
    Montrose is a city in western Colorado known for its access to outdoor recreation, including nearby national parks and scenic mountain landscapes.
  • D. Montrose
    Montrose is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
  • E. Montrose
    Montrose is a small borough in northeastern Pennsylvania that serves as the administrative and commercial center of Susquehanna County.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf1ab8c8190a51f498bfda957d8 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63464486c819085452675a43785b1 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:52 p.m.