Triple

T17849430
Position Surface form Disambiguated ID Type / Status
Subject Puhuangyu station E445756 entity
Predicate hasStationCodeLine5 P1289 FINISHED
Object Line 5 station code (Beijing Subway) 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: Line 5 station code (Beijing Subway) | Statement: [Puhuangyu station, hasStationCodeLine5, Line 5 station code (Beijing Subway)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasStationCodeLine5
Context triple: [Puhuangyu station, hasStationCodeLine5, Line 5 station code (Beijing Subway)]
  • A. hasStationCode chosen
    Indicates that an entity is associated with a specific station identification code.
  • B. hasAdjacentStationOnLine50
    Indicates that one station is directly next to another station along transit line 50.
  • C. hasStationCodeSystem
    Indicates that an entity uses or is associated with a particular system for assigning or managing station codes.
  • D. hasAdjacentStationOnLine54
    Indicates that one station is directly next to another station along transit line 54.
  • E. precededByStationOnLine5
    Indicates that one station directly comes before another station in the ordered sequence of stations on line 5.
  • 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffd7e2c81909a42cc7ab64e7db9 completed April 19, 2026, 8:19 a.m.
PD Predicate disambiguation batch_69e3d8e266888190ae976b4b7d5b886f completed April 18, 2026, 7:17 p.m.
Created at: April 10, 2026, 10:16 a.m.