Triple

T17829888
Position Surface form Disambiguated ID Type / Status
Subject Dongsi station E445222 entity
Predicate hasNativeName P1435 FINISHED
Object 东四站
东四站 is a Beijing Subway station located in the Dongsi area of central Beijing, serving as an interchange between multiple metro lines.
 E1291492 NE FINISHED

How this triple was built (4 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: 东四站 | Statement: [Dongsi station, hasNativeName, 东四站]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 东四站
Context triple: [Dongsi station, hasNativeName, 东四站]
  • A. 三元桥站
    三元桥站 is a major interchange station in Beijing’s subway network, serving as a key transfer point between multiple metro lines and the airport express.
  • B. 朝阳门站
    朝阳门站 is a major Beijing Subway interchange station serving the central Chaoyangmen area and connecting multiple key metro lines.
  • C. 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.
  • D. Dongsi Shitiao station
    Dongsi Shitiao station is a Beijing Subway station located in central Beijing, serving as a key stop on the city's metro network.
  • E. Fuxingmen station
    Fuxingmen station is a major interchange stop on the Beijing Subway, serving as a key transfer point between multiple central city lines.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 东四站
Triple: [Dongsi station, hasNativeName, 东四站]
Generated description
东四站 is a Beijing Subway station located in the Dongsi area of central Beijing, serving as an interchange between multiple metro lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 东四站
Target entity description: 东四站 is a Beijing Subway station located in the Dongsi area of central Beijing, serving as an interchange between multiple metro lines.
  • A. 三元桥站
    三元桥站 is a major interchange station in Beijing’s subway network, serving as a key transfer point between multiple metro lines and the airport express.
  • B. 朝阳门站
    朝阳门站 is a major Beijing Subway interchange station serving the central Chaoyangmen area and connecting multiple key metro lines.
  • C. 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.
  • D. Dongsi Shitiao station
    Dongsi Shitiao station is a Beijing Subway station located in central Beijing, serving as a key stop on the city's metro network.
  • E. Fuxingmen station
    Fuxingmen station is a major interchange stop on the Beijing Subway, serving as a key transfer point between multiple central city lines.
  • F. None of above. chosen

Provenance (5 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48917c4d88190b919a4b75aed011c completed April 19, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0306f3b0b881909b460809ac3ada92 completed May 12, 2026, 10:54 a.m.
NEDg Description generation batch_6a030986606c819099a8ea86a3ef1c26 completed May 12, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_6a0309e9e0108190bc1f60ddacef20cc completed May 12, 2026, 11:07 a.m.
Created at: April 10, 2026, 10:15 a.m.