Triple

T2280457
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate hasDepot P2413 FINISHED
Object Can Boixeres depot
Can Boixeres depot is a maintenance and storage facility serving the Barcelona Metro network.
 E249585 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: Can Boixeres depot | Statement: [Barcelona Metro, hasDepot, Can Boixeres depot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Can Boixeres depot
Context triple: [Barcelona Metro, hasDepot, Can Boixeres depot]
  • A. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • B. Bachet depot
    Bachet depot is a major tram maintenance and storage facility serving the public transport system in Geneva, Switzerland.
  • C. Fontenay-sous-Bois depot
    Fontenay-sous-Bois depot is a maintenance and storage facility serving trains on Paris Métro Line 1, located in the eastern suburb of Fontenay-sous-Bois.
  • D. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • E. Zaragoza depot
    Zaragoza depot is a maintenance and storage facility serving trains of the Mexico City Metro 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: Can Boixeres depot
Triple: [Barcelona Metro, hasDepot, Can Boixeres depot]
Generated description
Can Boixeres depot is a maintenance and storage facility serving the Barcelona Metro network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Can Boixeres depot
Target entity description: Can Boixeres depot is a maintenance and storage facility serving the Barcelona Metro network.
  • A. Carnide depot
    Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
  • B. Bachet depot
    Bachet depot is a major tram maintenance and storage facility serving the public transport system in Geneva, Switzerland.
  • C. Fontenay-sous-Bois depot
    Fontenay-sous-Bois depot is a maintenance and storage facility serving trains on Paris Métro Line 1, located in the eastern suburb of Fontenay-sous-Bois.
  • D. Nopo Depot
    Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
  • E. Zaragoza depot
    Zaragoza depot is a maintenance and storage facility serving trains of the Mexico City Metro 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc21ac3d48190abef254e1c3f45e8 completed March 7, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71e48fb081908498f826167020a2 completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae72bf22088190a2c111a71eb0dda7 completed March 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69ae731ab8bc819090fac5b311cb5fe0 completed March 9, 2026, 7:13 a.m.
Created at: March 4, 2026, 7:48 p.m.