Triple

T3367325
Position Surface form Disambiguated ID Type / Status
Subject Zhichunlu station E70866 entity
Predicate servesDistrict P82 FINISHED
Object Haidian District E89575 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: Haidian District | Statement: [Zhichunlu station, servesDistrict, Haidian District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haidian District
Context triple: [Zhichunlu station, servesDistrict, Haidian District]
  • A. Haidian District chosen
    Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
  • B. Changping District
    Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
  • C. Heping District
    Heping District is a central urban district of Tianjin, China, known for its commercial centers, historic architecture, and role as a core administrative and cultural area of the city.
  • D. Daxing District
    Daxing District is a rapidly developing suburban district in southern Beijing, China, known for hosting the major Beijing Daxing International Airport and large-scale urban expansion.
  • E. Fengtai District
    Fengtai District is an urban district in southwestern Beijing, China, known for its mix of residential, industrial, and historical areas, including the site of the Marco Polo Bridge.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2890480819082fe2e3c2874cece completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6786a558819098973b8f10b7e7cb completed March 20, 2026, 3:28 p.m.
Created at: March 8, 2026, 3:13 p.m.