Triple

T2677737
Position Surface form Disambiguated ID Type / Status
Subject MRT Line 3 E56499 entity
Predicate alsoKnownAs P39 FINISHED
Object MRT-3 E277583 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: MRT-3 | Statement: [MRT Line 3, alsoKnownAs, MRT-3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MRT-3
Context triple: [MRT Line 3, alsoKnownAs, MRT-3]
  • A. Manila Light Rail Transit System chosen
    The Manila Light Rail Transit System is an urban rapid transit network in Metro Manila, Philippines, providing high-capacity rail services along key commuter corridors.
  • B. BTS Skytrain
    The BTS Skytrain is an elevated rapid transit system that serves as one of Bangkok’s primary urban rail networks, helping alleviate traffic congestion and connect key commercial and residential areas across the city.
  • 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. MRT
    MRT is the three-letter ISO 3166-1 alpha-3 country code assigned to Mauritania.
  • E. RTA Marine transport system
    The RTA Marine transport system is Dubai’s government-operated network of water-based public transit services, including water buses, abras, and water taxis, that connect key locations along the city’s waterways.
  • 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_69ab4a4b13fc81909dfdb3f23da46832 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9b697fc8190a5ec8b75ee2ad238 completed March 7, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa065a6f48190973a3b6c52aa23bf completed March 10, 2026, 4:39 a.m.
Created at: March 6, 2026, 9:54 p.m.