Triple
T2280459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcelona Metro |
E51267
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object |
Zona Franca depot
Zona Franca depot is a maintenance and storage facility serving trains of the Barcelona Metro network.
|
E249587
|
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: Zona Franca depot | Statement: [Barcelona Metro, hasDepot, Zona Franca depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zona Franca depot Context triple: [Barcelona Metro, hasDepot, Zona Franca depot]
-
A.
Ticomán depot
Ticomán depot is a maintenance and storage facility serving trains of the Mexico City Metro system.
-
B.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
D.
Nopo Depot
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
E.
O’Higgins Station
O’Higgins Station is a Chilean Antarctic research base located on the Antarctic Peninsula, used primarily for scientific studies and maintaining Chile’s presence in the region.
- 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: Zona Franca depot Triple: [Barcelona Metro, hasDepot, Zona Franca depot]
Generated description
Zona Franca depot is a maintenance and storage facility serving trains of the Barcelona Metro network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zona Franca depot Target entity description: Zona Franca depot is a maintenance and storage facility serving trains of the Barcelona Metro network.
-
A.
Ticomán depot
Ticomán depot is a maintenance and storage facility serving trains of the Mexico City Metro system.
-
B.
Pontinha depot
Pontinha depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
C.
Carnide depot
Carnide depot is a maintenance and storage facility serving the Lisbon Metro system in Lisbon, Portugal.
-
D.
Nopo Depot
Nopo Depot is a maintenance and storage facility serving the Busan Metro system in Busan, South Korea.
-
E.
O’Higgins Station
O’Higgins Station is a Chilean Antarctic research base located on the Antarctic Peninsula, used primarily for scientific studies and maintaining Chile’s presence in the region.
- 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.