Triple

T7656544
Position Surface form Disambiguated ID Type / Status
Subject Tokyo metropolitan rail network E173398 entity
Predicate includes P1393 FINISHED
Object Tama Monorail E193100 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: Tama Monorail | Statement: [Tokyo metropolitan rail network, includes, Tama Monorail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tama Monorail
Context triple: [Tokyo metropolitan rail network, includes, Tama Monorail]
  • A. Tama Monorail chosen
    Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
  • B. Tokyo Monorail
    Tokyo Monorail is an urban transit line in Tokyo that provides rapid rail service between central Tokyo and Haneda Airport.
  • C. KL Monorail
    KL Monorail is an elevated urban rail line in Kuala Lumpur that provides rapid transit service through the city’s central and commercial districts.
  • D. Osaka Monorail
    Osaka Monorail is a straddle-beam monorail system in Osaka Prefecture, Japan, serving as a major urban transit line linking key suburbs, commercial areas, and transport hubs.
  • E. Alweg Monorail
    The Alweg Monorail is an elevated monorail system in Seattle that became an iconic symbol of mid-20th-century futuristic transportation design.
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018fcbb48190a479f2effd939a8e completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a21dd3088190bb026de65970a14b completed March 29, 2026, 3:53 a.m.
Created at: March 27, 2026, 3:59 p.m.