Triple
T22744279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcelona Metro Line 2 |
E562504
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Verneda station
Verneda station is a rapid transit stop on Barcelona's Metro network serving the Sant Adrià de Besòs area on Line 2.
|
E1552545
|
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 station | Statement: [Barcelona Metro Line 2, hasStation, Verneda station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verneda station Context triple: [Barcelona Metro Line 2, hasStation, Verneda station]
-
A.
Bulnes station
Bulnes station is a stop on Buenos Aires’ underground network, serving passengers on Line D in the Palermo area.
-
B.
Olleros station
Olleros station is a stop on Buenos Aires’ Line D subway, serving the Palermo and Colegiales neighborhoods in Argentina’s capital.
-
C.
Valldaura station
Valldaura station is an underground stop on the Barcelona Metro network located in the Horta-Guinardó district of the city.
-
D.
Mirador station
Mirador station is a stop on Santiago, Chile’s Metro system, serving passengers on Line 5 in the city’s urban transit network.
-
E.
Águeda station
Águeda station is a railway station in the city of Águeda, Portugal, serving passengers on the narrow-gauge Vouga Line.
- 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 station Triple: [Barcelona Metro Line 2, hasStation, Verneda station]
Generated description
Verneda station is a rapid transit stop on Barcelona's Metro network serving the Sant Adrià de Besòs area on Line 2.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verneda station Target entity description: Verneda station is a rapid transit stop on Barcelona's Metro network serving the Sant Adrià de Besòs area on Line 2.
-
A.
Bulnes station
Bulnes station is a stop on Buenos Aires’ underground network, serving passengers on Line D in the Palermo area.
-
B.
Olleros station
Olleros station is a stop on Buenos Aires’ Line D subway, serving the Palermo and Colegiales neighborhoods in Argentina’s capital.
-
C.
Valldaura station
Valldaura station is an underground stop on the Barcelona Metro network located in the Horta-Guinardó district of the city.
-
D.
Mirador station
Mirador station is a stop on Santiago, Chile’s Metro system, serving passengers on Line 5 in the city’s urban transit network.
-
E.
Águeda station
Águeda station is a railway station in the city of Águeda, Portugal, serving passengers on the narrow-gauge Vouga Line.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1797590f08190a784f73fcd27b101 |
completed | April 29, 2026, 3:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b8fd41bcc81909e23e380bf834ca5 |
completed | May 18, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_6a0b93d4b8e08190a0542ffc42f12814 |
completed | May 18, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b94bbb9c88190a7ab0937d1b398a5 |
completed | May 18, 2026, 10:37 p.m. |
Created at: April 17, 2026, 3:23 p.m.