Triple

T2986825
Position Surface form Disambiguated ID Type / Status
Subject Ankara Metro E80644 entity
Predicate hasLine P35 FINISHED
Object 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.
E318109 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: M2 line | Statement: [Ankara Metro, hasLine, M2 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: M2 line
Context triple: [Ankara Metro, hasLine, M2 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. Metro Line B
    Metro Line B is a rapid transit line that forms part of the Mexico City Metro network.
  • C. Metro Line 5
    Metro Line 5 is a rapid transit route within a city's metro system that connects with Metro Line 6 at one or more interchange stations.
  • D. Metro Line 3
    Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
  • E. Metro A Line
    The Metro A Line is a light rail line in Los Angeles County that runs between downtown Los Angeles and Long Beach as part of the region’s Metro Rail system.
  • 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: M2 line
Triple: [Ankara Metro, hasLine, M2 line]
Generated description
The M2 line is a major rapid transit route within the Ankara Metro system in Turkey, serving key districts of the capital city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: M2 line
Target entity description: The M2 line is a major rapid transit route within the Ankara Metro system in Turkey, serving key districts of the capital city.
  • 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. Metro Line B
    Metro Line B is a rapid transit line that forms part of the Mexico City Metro network.
  • C. Metro Line 5
    Metro Line 5 is a rapid transit route within a city's metro system that connects with Metro Line 6 at one or more interchange stations.
  • D. Metro Line 3
    Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
  • E. Metro A Line
    The Metro A Line is a light rail line in Los Angeles County that runs between downtown Los Angeles and Long Beach as part of the region’s Metro Rail system.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c88f608190bf734e0b744bf3d1 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e3654388190beeb1c6b2a629b85 completed March 11, 2026, 8:56 a.m.
NEDg Description generation batch_69b12f26a8d08190be6023fb7e3ddee9 completed March 11, 2026, 9 a.m.
NED2 Entity disambiguation (via description) batch_69b1cb268d9881908766e50524b208cc completed March 11, 2026, 8:05 p.m.
Created at: March 8, 2026, 2:59 p.m.