Triple

T10574764
Position Surface form Disambiguated ID Type / Status
Subject Line 2 (Barcelona Metro) E249579 entity
Predicate hasStation P35 FINISHED
Object La Pau
La Pau is a Barcelona Metro station that serves as a key interchange and terminus in the city’s northeastern Sant Martí district.
E871710 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: La Pau | Statement: [Line 2 (Barcelona Metro), hasStation, La Pau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Pau
Context triple: [Line 2 (Barcelona Metro), hasStation, La Pau]
  • A. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • B. La Dôle
    La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
  • C. Léognan
    Léognan is a renowned wine-producing commune in southwestern France, celebrated for its prestigious red and white Bordeaux wines.
  • D. La Sarraz
    La Sarraz is a small town in the canton of Vaud, Switzerland, known for its historic castle and role as a cultural and intellectual meeting place.
  • E. Piossasco
    Piossasco is a municipality in the Metropolitan City of Turin in the Piedmont region of northwestern Italy.
  • 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: La Pau
Triple: [Line 2 (Barcelona Metro), hasStation, La Pau]
Generated description
La Pau is a Barcelona Metro station that serves as a key interchange and terminus in the city’s northeastern Sant Martí district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: La Pau
Target entity description: La Pau is a Barcelona Metro station that serves as a key interchange and terminus in the city’s northeastern Sant Martí district.
  • A. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • B. La Dôle
    La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
  • C. Léognan
    Léognan is a renowned wine-producing commune in southwestern France, celebrated for its prestigious red and white Bordeaux wines.
  • D. La Sarraz
    La Sarraz is a small town in the canton of Vaud, Switzerland, known for its historic castle and role as a cultural and intellectual meeting place.
  • E. Piossasco
    Piossasco is a municipality in the Metropolitan City of Turin in the Piedmont region of northwestern Italy.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52749dda08190b0c9627a931c5848 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b5d89748190bb398943e4a16e9b completed April 10, 2026, 7:11 p.m.
NEDg Description generation batch_69d94e1502108190a81bfa1d5a425e5a completed April 10, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_69d94f0bb6888190b4038df6dcd96d33 completed April 10, 2026, 7:27 p.m.
Created at: April 6, 2026, 12:38 p.m.