Triple

T7175694
Position Surface form Disambiguated ID Type / Status
Subject Istanbul Metro E167312 entity
Predicate hasLine P35 FINISHED
Object M50 line
The M50 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's expanding urban rail network.
 E672933 NE FINISHED

How this triple was built (4 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: M50 line | Statement: [Istanbul Metro, hasLine, M50 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M50 line
Context triple: [Istanbul Metro, hasLine, M50 line]
  • A. M5 line
    The M5 line is a fully automated, driverless metro line forming part of Istanbul's rapid transit network on the Asian side of the city.
  • B. M35 line
    The M35 line is a metro route within the Istanbul Metro system that serves as part of the city's rapid transit network.
  • C. M16 line
    The M16 line is a rapid transit route within the Istanbul Metro system that serves passengers in Turkey’s largest city.
  • D. 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.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: M50 line
Triple: [Istanbul Metro, hasLine, M50 line]
Generated description
The M50 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's expanding urban rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M50 line
Target entity description: The M50 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's expanding urban rail network.
  • A. M5 line
    The M5 line is a fully automated, driverless metro line forming part of Istanbul's rapid transit network on the Asian side of the city.
  • B. M35 line chosen
    The M35 line is a metro route within the Istanbul Metro system that serves as part of the city's rapid transit network.
  • C. M16 line
    The M16 line is a rapid transit route within the Istanbul Metro system that serves passengers in Turkey’s largest city.
  • D. 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.
  • E. 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.
  • F. None of above.

Provenance (5 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_69c861296e5c8190aa2a189e71963de9 completed March 28, 2026, 11:15 p.m.
NEDg Description generation batch_69c862466fd481908ea5772e76a88d95 completed March 28, 2026, 11:20 p.m.
NED2 Entity disambiguation (via description) batch_69c862cae0448190859a07db338e1de7 completed March 28, 2026, 11:22 p.m.
Created at: March 27, 2026, 2:48 p.m.