Triple

T36392891
Position Surface form Disambiguated ID Type / Status
Subject Union Street E896376 entity
Predicate servesTrains P154206 FINISHED
Object R 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: R | Statement: [Union Street, servesTrains, R]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: servesTrains
Context triple: [Union Street, servesTrains, R]
  • A. trainsOn
    Indicates that one entity receives training, instruction, or practice using or based on another entity (such as a resource, dataset, tool, or subject).
  • B. servedByNamedTrain
    Indicates that a service, route, or journey is operated specifically by a train with a particular designated name.
  • C. servesLocalTrains
    Indicates that a station or facility provides service or stops specifically for local (non-express) train routes.
  • D. hasRailServiceAt chosen
    Indicates that a rail transport service operates at or serves a particular location or facility.
  • E. railwayTypeServed
    Indicates the type of railway system or service that a given entity (such as a station, line, or facility) is designed to serve or accommodate.
  • 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_69f76e52e3108190becf70b090ae7bd6 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_6a0041860fd081908623ef9fd40a9775 completed May 10, 2026, 8:27 a.m.
PD Predicate disambiguation batch_6a00414b01488190a312adb3b25d69cf completed May 10, 2026, 8:26 a.m.
Created at: May 3, 2026, 4:10 p.m.