Triple

T11014608
Position Surface form Disambiguated ID Type / Status
Subject LRT Ampang Line E260330 entity
Predicate connectsWith P37 FINISHED
Object KL Monorail E258908 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: KL Monorail | Statement: [LRT Ampang Line, connectsWith, KL Monorail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KL Monorail
Context triple: [LRT Ampang Line, connectsWith, KL Monorail]
  • A. KL Monorail chosen
    KL Monorail is an elevated urban rail line in Kuala Lumpur that provides rapid transit service through the city’s central and commercial districts.
  • B. Tama Monorail
    Tama Monorail is a straddle-beam monorail line in Tokyo, Japan, providing urban transit service through the Tama area.
  • C. Tokyo Monorail
    Tokyo Monorail is an urban transit line in Tokyo that provides rapid rail service between central Tokyo and Haneda Airport.
  • D. Okinawa Urban Monorail
    Okinawa Urban Monorail is an elevated rail transit system serving the city of Naha and surrounding areas on Japan’s Okinawa Island.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797a49f648190a5144625d09dec6f completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374c238ac81908e0a5eff958d6545 completed April 18, 2026, 12:10 p.m.
Created at: April 8, 2026, 9:25 p.m.