Triple

T17402630
Position Surface form Disambiguated ID Type / Status
Subject Line 16 (Beijing Subway) E423130 entity
Predicate servesArea P82 FINISHED
Object Xicheng District 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: Xicheng District | Statement: [Line 16 (Beijing Subway), servesArea, Xicheng District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xicheng District
Context triple: [Line 16 (Beijing Subway), servesArea, Xicheng District]
  • A. Xicheng District chosen
    Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
  • B. Chengdong District
    Chengdong District is an urban administrative district of Xining, the capital city of Qinghai Province in northwestern China.
  • C. Shuangxi District
    Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
  • D. Chengzhong District
    Chengzhong District is a central urban district of Xining, the capital city of Qinghai Province in northwest China.
  • E. Wensheng District
    Wensheng District is an urban district within the prefecture-level city of Liaoyang in Liaoning Province, northeastern China.
  • 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_69d889d710288190bf0f4762801fefae completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43b046ad88190a95bbeda4e602514 completed April 19, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:45 a.m.