Triple

T7175648
Position Surface form Disambiguated ID Type / Status
Subject Istanbul Metro E167312 entity
Predicate hasLine P35 FINISHED
Object M3 line E320161 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: M3 line | Statement: [Istanbul Metro, hasLine, M3 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M3 line
Context triple: [Istanbul Metro, hasLine, M3 line]
  • A. M3 line chosen
    The M3 line is a rapid transit route within the Ankara Metro system serving parts of Turkey’s capital city.
  • B. M2 line
    The M2 line is a major rapid transit route within the Ankara Metro system in Turkey, serving key districts of the capital city.
  • C. M2 line
    The M2 line is a fully automated metro line in Lausanne, Switzerland, running on a steep north–south route that connects the city center with surrounding districts and the lakeshore.
  • D. M2 line
    The M2 line is one of the main lines of the Helsinki Metro rapid transit system, serving key districts across the Helsinki metropolitan area.
  • E. M2 line
    The M2 line is a major rapid transit route of the Istanbul Metro system that runs in a north–south direction, connecting key districts on the European side of the city.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88ec6a8819083cbc3f4c39b8c79 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbdf32d48190a2d24914c3529160 completed March 28, 2026, 12:38 p.m.
Created at: March 27, 2026, 2:48 p.m.