Triple

T8174378
Position Surface form Disambiguated ID Type / Status
Subject NRT E190904 entity
Predicate railServicesInclude P21523 FINISHED
Object Keisei Skyliner E235302 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: Keisei Skyliner | Statement: [NRT, railServicesInclude, Keisei Skyliner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keisei Skyliner
Context triple: [NRT, railServicesInclude, Keisei Skyliner]
  • A. Keisei Skyliner chosen
    Keisei Skyliner is a high-speed limited express train service in Japan that links central Tokyo with Narita International Airport.
  • B. Rokkō Liner
    Rokkō Liner is an automated guideway transit line in Kobe, Japan, connecting the artificial island of Rokkō Island with the mainland.
  • C. Narita Express
    Narita Express is a limited express train service in Japan that provides fast, direct rail connections between central Tokyo and Narita International Airport.
  • D. Tsukuba Express
    Tsukuba Express is a high-speed commuter railway line in Japan connecting central Tokyo with the city of Tsukuba in Ibaraki Prefecture.
  • E. Haruka limited express
    Haruka limited express is a Japanese limited express train service connecting Kansai International Airport with major destinations such as Kyoto and Osaka, primarily serving airport travelers.
  • 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_69ca82c1c0a08190bf8692b4d91a03ca completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb7266bc148190984060b7b95effb5 completed March 31, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94bbdc288190aee5187e95ca7a8d completed April 1, 2026, 9:57 p.m.
Created at: March 30, 2026, 5:40 p.m.