Triple

T7175706
Position Surface form Disambiguated ID Type / Status
Subject Istanbul Metro E167312 entity
Predicate firstLineOpened P17696 FINISHED
Object M1 line E646533 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: M1 line | Statement: [Istanbul Metro, firstLineOpened, M1 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M1 line
Context triple: [Istanbul Metro, firstLineOpened, M1 line]
  • A. M1 line
    The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
  • B. M1 line
    The M1 line is one of the main lines of the Helsinki Metro, running east–west through the Helsinki region and serving several key suburban and central stations.
  • C. M1 line
    The M1 line is a light metro route in Lausanne, Switzerland, connecting the city center with the university and lakeside areas as part of the Lausanne Métro network.
  • D. M1 line chosen
    The M1 line is one of the main rapid transit routes of the Istanbul Metro, connecting central districts with key transport hubs such as the airport and intercity bus terminal.
  • E. 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.
  • 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_69c8569fbf4081909897b0e5456cd66a completed March 28, 2026, 10:30 p.m.
Created at: March 27, 2026, 2:48 p.m.