Triple

T15187657
Position Surface form Disambiguated ID Type / Status
Subject Fuxingmen commercial area E362918 entity
Predicate servedBy P82 FINISHED
Object Fuxingmen Station E73684 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: Fuxingmen Station | Statement: [Fuxingmen commercial area, servedBy, Fuxingmen Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fuxingmen Station
Context triple: [Fuxingmen commercial area, servedBy, Fuxingmen Station]
  • A. Fuxingmen station chosen
    Fuxingmen station is a major interchange stop on the Beijing Subway, serving as a key transfer point between multiple central city lines.
  • B. Chongwenmen station
    Chongwenmen station is a major interchange stop on the Beijing Subway serving central Beijing near the historic Chongwenmen gate area.
  • C. Hepingmen station
    Hepingmen station is an underground metro station on the Beijing Subway serving the central Xicheng District near historic commercial and cultural areas.
  • D. Dongzhimen station
    Dongzhimen station is a major Beijing Subway interchange hub connecting multiple lines and serving as a key gateway to the city’s northeastern districts and the airport rail link.
  • E. 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.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067995fc8190b048f15086bd42f0 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe60d4a08190833397c75b56932c completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 3:09 a.m.