Triple

T8048313
Position Surface form Disambiguated ID Type / Status
Subject Line 6 (Tehran Metro) E187609 entity
Predicate hasStation P35 FINISHED
Object Kargar station
Kargar station is a metro stop on Tehran’s urban rail network serving passengers along Line 6.
 E706478 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: Kargar station | Statement: [Line 6 (Tehran Metro), hasStation, Kargar station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kargar station
Context triple: [Line 6 (Tehran Metro), hasStation, Kargar station]
  • A. Konak station
    Konak station is a central underground stop on the İzmir Metro system, serving as one of the main transit hubs in the heart of İzmir, Turkey.
  • B. Hamar Station
    Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
  • C. Kaladar Station
    Kaladar Station is a small rural community within the township of Addington Highlands in eastern Ontario, Canada.
  • D. Kazlıçeşme station
    Kazlıçeşme station is a major railway and commuter rail stop in Istanbul that serves as one of the key terminals on the Marmaray cross-Bosphorus rail system.
  • E. Fahrettin Altay station
    Fahrettin Altay station is a major western terminus and transfer hub on the İzmir Metro system in İzmir, Turkey.
  • 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: Kargar station
Triple: [Line 6 (Tehran Metro), hasStation, Kargar station]
Generated description
Kargar station is a metro stop on Tehran’s urban rail network serving passengers along Line 6.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kargar station
Target entity description: Kargar station is a metro stop on Tehran’s urban rail network serving passengers along Line 6.
  • A. Konak station
    Konak station is a central underground stop on the İzmir Metro system, serving as one of the main transit hubs in the heart of İzmir, Turkey.
  • B. Hamar Station
    Hamar Station is a railway station in the town of Hamar in Innlandet county, Norway, serving as a regional transport hub on the country’s rail network.
  • C. Kaladar Station
    Kaladar Station is a small rural community within the township of Addington Highlands in eastern Ontario, Canada.
  • D. Kazlıçeşme station
    Kazlıçeşme station is a major railway and commuter rail stop in Istanbul that serves as one of the key terminals on the Marmaray cross-Bosphorus rail system.
  • E. Fahrettin Altay station
    Fahrettin Altay station is a major western terminus and transfer hub on the İzmir Metro system in İzmir, Turkey.
  • 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_69ca82b15e948190a62fd7af5218426a completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f7711f48190af2002533c2e426a completed March 31, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5716934481908ec60cc9fd825ad7 completed March 31, 2026, 11:21 p.m.
NEDg Description generation batch_69cc58acba3c8190b7d09aa23b5f10f8 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5ccee5648190a8ebdf8029eded98 completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:24 p.m.