Triple

T17402633
Position Surface form Disambiguated ID Type / Status
Subject Line 16 (Beijing Subway) E423130 entity
Predicate stationServed P6301 FINISHED
Object National Library station 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: National Library station | Statement: [Line 16 (Beijing Subway), stationServed, National Library station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: National Library station
Context triple: [Line 16 (Beijing Subway), stationServed, National Library station]
  • A. National Library station chosen
    National Library station is a major interchange stop on the Beijing Subway serving the area around China's National Library in the Haidian District.
  • B. NHK Radio 1
    NHK Radio 1 is Japan’s primary national radio station operated by NHK, offering news, current affairs, and public service programming across the country.
  • C. NHK-FM
    NHK-FM is Japan’s national public FM radio network operated by NHK, known for its focus on classical music, jazz, and cultural programming.
  • D. NHK Radio 2
    NHK Radio 2 is a Japanese public radio station operated by NHK that focuses on educational, cultural, and language-learning programming.
  • E. La Cultura station
    La Cultura station is a stop on Line 1 of the Lima Metro serving the La Victoria/San Borja area of Lima, Peru.
  • 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.