Triple

T7175652
Position Surface form Disambiguated ID Type / Status
Subject Istanbul Metro E167312 entity
Predicate hasLine P35 FINISHED
Object M7 line
The M7 line is a fully automated rapid transit route in the Istanbul Metro system that serves the city’s European side.
 E657400 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: M7 line | Statement: [Istanbul Metro, hasLine, M7 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M7 line
Context triple: [Istanbul Metro, hasLine, M7 line]
  • A. M4 line
    The M4 line is a rapid transit route of the Istanbul Metro system serving the city’s Asian side.
  • B. M4 line
    The M4 line is a rapid transit route within the Ankara Metro system serving passengers in Turkey’s capital city.
  • C. M6 line
    The M6 line is a short light metro route in Istanbul that connects the Levent area to the Boğaziçi University–Hisarüstü district on the European side of the city.
  • D. 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.
  • E. M1 line
    The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
  • 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: M7 line
Triple: [Istanbul Metro, hasLine, M7 line]
Generated description
The M7 line is a fully automated rapid transit route in the Istanbul Metro system that serves the city’s European side.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M7 line
Target entity description: The M7 line is a fully automated rapid transit route in the Istanbul Metro system that serves the city’s European side.
  • A. M4 line
    The M4 line is a rapid transit route of the Istanbul Metro system serving the city’s Asian side.
  • B. M4 line
    The M4 line is a rapid transit route within the Ankara Metro system serving passengers in Turkey’s capital city.
  • C. M6 line
    The M6 line is a short light metro route in Istanbul that connects the Levent area to the Boğaziçi University–Hisarüstü district on the European side of the city.
  • D. 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.
  • E. M1 line
    The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
  • F. None of above. chosen

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_69c7eec651a48190b52052bfef83ffcd completed March 28, 2026, 3:07 p.m.
NEDg Description generation batch_69c7f06173f481908faf95824827f1a9 completed March 28, 2026, 3:14 p.m.
NED2 Entity disambiguation (via description) batch_69c7f11f2b208190b235b9800a63faed completed March 28, 2026, 3:17 p.m.
Created at: March 27, 2026, 2:48 p.m.