Triple

T2677664
Position Surface form Disambiguated ID Type / Status
Subject Araneta City E56497 entity
Predicate servedBy P82 FINISHED
Object LRT Line 2 E57808 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: LRT Line 2 | Statement: [Araneta City, servedBy, LRT Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LRT Line 2
Context triple: [Araneta City, servedBy, LRT Line 2]
  • A. LRT Line 2 chosen
    LRT Line 2 is an elevated rapid transit line in Metro Manila, Philippines, running east–west and serving major areas including Quezon City, Manila, and Pasig.
  • B. LRT Line 1
    LRT Line 1 is a major elevated urban rail line in Metro Manila, Philippines, forming part of the city’s light rail transit system and serving as a key north–south transport corridor.
  • C. MRT Line 3
    MRT Line 3 is a major elevated rapid transit line in Metro Manila that runs along EDSA, serving as one of the region’s primary commuter rail corridors.
  • D. Metro Line 3
    Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
  • E. RTA Waterfront Line
    The RTA Waterfront Line is a light rail line in Cleveland, Ohio, that connects downtown with the city's waterfront attractions and nearby neighborhoods.
  • 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.