Triple

T4185103
Position Surface form Disambiguated ID Type / Status
Subject Ahmedabad Metro E88290 entity
Predicate depot P14646 FINISHED
Object Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
E418889 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: Vastral Depot | Statement: [Ahmedabad Metro, depot, Vastral Depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vastral Depot
Context triple: [Ahmedabad Metro, depot, Vastral Depot]
  • A. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • B. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • C. Fürth depot
    Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
  • D. Cronenbourg depot
    Cronenbourg depot is a major maintenance and storage facility for the Strasbourg tramway network in Strasbourg, France.
  • E. Pontinha depot
    Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • 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: Vastral Depot
Triple: [Ahmedabad Metro, depot, Vastral Depot]
Generated description
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vastral Depot
Target entity description: Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
  • A. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • B. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • C. Fürth depot
    Fürth depot is a maintenance and storage facility serving the Nuremberg U-Bahn rapid transit system in the Fürth area of Germany.
  • D. Cronenbourg depot
    Cronenbourg depot is a major maintenance and storage facility for the Strasbourg tramway network in Strasbourg, France.
  • E. Pontinha depot
    Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af032318bc81908345db0753f8ba66 completed March 9, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589fe4b508190a1c5a1d426245ede completed March 14, 2026, 4:17 p.m.
NEDg Description generation batch_69b58a64e67081909d9c03c8f92b4f7e completed March 14, 2026, 4:18 p.m.
NED2 Entity disambiguation (via description) batch_69b58aeb4f848190aa8d8511c3b63eaa completed March 14, 2026, 4:20 p.m.
Created at: March 9, 2026, 3:45 p.m.