Triple
T10574765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 2 (Barcelona Metro) |
E249579
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Verneda
Verneda is a Barcelona Metro station on the city's Line 2 serving the Verneda neighborhood in the Sant Adrià de Besòs area.
|
E871711
|
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: Verneda | Statement: [Line 2 (Barcelona Metro), hasStation, Verneda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verneda Context triple: [Line 2 (Barcelona Metro), hasStation, Verneda]
-
A.
Peralillo
Peralillo is a rural municipality and town in central Chile’s Colchagua wine-growing region, known for its agricultural production and vineyards.
-
B.
Caleruega
Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
-
C.
Villablino
Villablino is a municipality and former mining town in northwestern Spain, known for its mountainous surroundings and location in the Laciana valley of the Province of León.
-
D.
Ocaña
Ocaña is a historic city in northeastern Colombia known for its colonial architecture and role in the country’s independence-era events.
-
E.
Ocaña
Ocaña is a historic town in central Spain known for its large Plaza Mayor and its role as a regional cultural and commercial center.
- 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: Verneda Triple: [Line 2 (Barcelona Metro), hasStation, Verneda]
Generated description
Verneda is a Barcelona Metro station on the city's Line 2 serving the Verneda neighborhood in the Sant Adrià de Besòs area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verneda Target entity description: Verneda is a Barcelona Metro station on the city's Line 2 serving the Verneda neighborhood in the Sant Adrià de Besòs area.
-
A.
Peralillo
Peralillo is a rural municipality and town in central Chile’s Colchagua wine-growing region, known for its agricultural production and vineyards.
-
B.
Caleruega
Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
-
C.
Villablino
Villablino is a municipality and former mining town in northwestern Spain, known for its mountainous surroundings and location in the Laciana valley of the Province of León.
-
D.
Ocaña
Ocaña is a historic city in northeastern Colombia known for its colonial architecture and role in the country’s independence-era events.
-
E.
Ocaña
Ocaña is a historic town in central Spain known for its large Plaza Mayor and its role as a regional cultural and commercial center.
- 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.