Triple

T17916604
Position Surface form Disambiguated ID Type / Status
Subject Zhuxinzhuang station E447941 entity
Predicate isKeyStopOn P3386 FINISHED
Object Line 8 — NE NERFINISHED

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 8 | Statement: [Zhuxinzhuang station, isKeyStopOn, Line 8]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 8
Context triple: [Zhuxinzhuang station, isKeyStopOn, Line 8]
  • A. Line 8 chosen
    Line 8 is a rapid transit line of the Beijing Subway system that serves key central and northern districts of Beijing.
  • B. Line 8
    Line 8 is a line of the Mexico City Metro system that runs in a generally north–south direction, connecting key residential and commercial areas of the city.
  • C. Line 8
    Line 8 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's key urban rail corridors.
  • D. Line 8
    Line 8 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as part of the city's expanding urban rail network.
  • E. Line 8
    Line 8 is a route of the Seoul Metropolitan Subway system that serves southeastern parts of Seoul and nearby areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f6d394819082a6d69fd1e23d2f completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a3062bfc819083f7c0521bad4db8 completed April 19, 2026, 9:40 a.m.
Created at: April 10, 2026, 10:20 a.m.