Triple

T14247397
Position Surface form Disambiguated ID Type / Status
Subject Opera station E353170 entity
Predicate servedByLine P1293 FINISHED
Object M1 line E1081259 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: [Opera station, servedByLine, M1 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M1 line
Context triple: [Opera station, servedByLine, 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 chosen
    The M1 line is one of the main lines of the Copenhagen Metro, connecting central Copenhagen with districts such as Ørestad and Vestamager.
  • D. 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.
  • E. M1 line
    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.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de629464f88190817b190731bab156 completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd282571ec819080d187ecec3ed925 completed May 8, 2026, 12:02 a.m.
Created at: April 10, 2026, 1:08 a.m.