Triple

T4204907
Position Surface form Disambiguated ID Type / Status
Subject Naha Station E86159 entity
Predicate railwayOperator P5620 FINISHED
Object Okinawa Urban Monorail E93549 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: Okinawa Urban Monorail | Statement: [Naha Station, railwayOperator, Okinawa Urban Monorail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Okinawa Urban Monorail
Context triple: [Naha Station, railwayOperator, Okinawa Urban Monorail]
  • A. Okinawa Urban Monorail chosen
    Okinawa Urban Monorail is an elevated rail transit system serving the city of Naha and surrounding areas on Japan’s Okinawa Island.
  • B. 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.
  • C. Tokyo Monorail
    Tokyo Monorail is an urban transit line in Tokyo that provides rapid rail service between central Tokyo and Haneda Airport.
  • D. Tama Monorail
    Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
  • E. 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.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0382eafc8190946bf45bf28095dd completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b596258db88190aed602eeb2323fee completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:49 p.m.