Triple

T27905031
Position Surface form Disambiguated ID Type / Status
Subject Knapps Narrows Bridge E705745 entity
Predicate crossesUse P27425 FINISHED
Object navigation channel LITERAL 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: navigation channel | Statement: [Knapps Narrows Bridge, crossesUse, navigation channel]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: crossesUse
Context triple: [Knapps Narrows Bridge, crossesUse, navigation channel]
  • A. crossesIn chosen
    Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
  • B. crossesTo
    Indicates that one entity moves or extends from one side or area to another, passing over or through some boundary or intervening space.
  • C. crossesBetween
    Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
  • D. crossesNear
    Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
  • E. usedCross
    Indicates that one entity made use of a cross-shaped object or structure, or traversed by means of a crossing point such as a crosswalk or intersection.
  • F. None of above.

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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f6aaf50be08190a2b62a6d881f8aee completed May 3, 2026, 1:55 a.m.
PD Predicate disambiguation batch_69f6aa1c555081908787dbf76147f180 completed May 3, 2026, 1:51 a.m.
Created at: April 27, 2026, 6:45 p.m.