Triple

T3176448
Position Surface form Disambiguated ID Type / Status
Subject Line 4 (Beijing Subway) E66475 entity
Predicate hasStation P35 FINISHED
Object Xuanwumen station E350025 NE 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: Xuanwumen station | Statement: [Line 4 (Beijing Subway), hasStation, Xuanwumen station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xuanwumen station
Context triple: [Line 4 (Beijing Subway), hasStation, Xuanwumen station]
  • A. Xuanwumen station chosen
    Xuanwumen station is a major interchange stop on the Beijing Subway, serving as a key transfer point near central Beijing.
  • B. Fuchengmen station
    Fuchengmen station is an underground metro station in Beijing serving the central Xicheng District as part of the city’s extensive subway network.
  • C. Xizhimen station
    Xizhimen station is a major interchange hub in the Beijing Subway system, connecting multiple lines and serving the busy Xizhimen commercial and transport area.
  • D. Chongwenmen station
    Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
  • E. Chaoyangmen station
    Chaoyangmen station is a major interchange stop on the Beijing Subway serving the central Chaoyangmen area of Beijing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada69b0bec8190957913b44d876079 completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533595bb88190814ea2ebe3495525 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:06 p.m.