Triple

T38673477
Position Surface form Disambiguated ID Type / Status
Subject Niagara Falls border crossings system E943663 entity
Predicate includesTrafficType P146573 FINISHED
Object passenger vehicles 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: passenger vehicles | Statement: [Niagara Falls border crossings system, includesTrafficType, passenger vehicles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: includesTrafficType
Context triple: [Niagara Falls border crossings system, includesTrafficType, passenger vehicles]
  • A. coversTrafficType chosen
    Indicates that one entity includes, handles, or applies to a specified type or category of traffic.
  • B. hasTrafficMode
    Indicates the mode or type of traffic associated with or applicable to an entity (e.g., pedestrian, vehicular, public transit).
  • C. hasCargoTrafficType
    Indicates that an entity is associated with a specific type or category of cargo traffic it handles or supports.
  • D. hasTrafficFeature
    Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
  • E. supportsTraffic
    Indicates that one entity is capable of handling, carrying, or accommodating the flow or volume of traffic associated with another entity.
  • 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_69f76eec28708190b9c82a505fc278e0 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_6a037c9141dc819098d7fcc36e69882c completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a037a2026248190b894436a578d79ac completed May 12, 2026, 7:06 p.m.
Created at: May 3, 2026, 4:33 p.m.