Triple
T11328161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Besòs |
E268276
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | Trambesòs |
E51772
|
NE FINISHED |
How this triple was built (2 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: Trambesòs | Statement: [Besòs, servedBy, Trambesòs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trambesòs Context triple: [Besòs, servedBy, Trambesòs]
-
A.
Trambesòs
chosen
Trambesòs is a modern tram network serving Barcelona’s northeastern metropolitan area, connecting the city with nearby coastal and suburban districts.
-
B.
Ripollès
Ripollès is a mountainous comarca in the Catalan Pyrenees of northeastern Spain, known for its Romanesque heritage, natural landscapes, and proximity to the French border.
-
C.
Camarasa
Camarasa is a municipality in the province of Lleida, Catalonia, Spain, known for its reservoir and scenic location in the Noguera region.
-
D.
Lluçanès
Lluçanès is a historical comarca in central Catalonia, known for its rural landscapes, small villages, and traditional Catalan culture.
-
E.
Noguès
Noguès is a French surname borne by various notable individuals, including figures in politics, arts, and sports.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e330008190b75490efde01dc59 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef127eaf588190aaca151ee4022f3c |
completed | April 27, 2026, 7:38 a.m. |
Created at: April 8, 2026, 9:32 p.m.