Triple
T10769176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallès Oriental |
E254029
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Caldes de Montbui
Caldes de Montbui is a historic spa town in Catalonia, Spain, renowned for its thermal springs and Roman-era heritage.
|
E1043212
|
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: Caldes de Montbui | Statement: [Vallès Oriental, contains, Caldes de Montbui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caldes de Montbui Context triple: [Vallès Oriental, contains, Caldes de Montbui]
-
A.
Calella
Calella is a coastal town and popular tourist destination on the Mediterranean in the Maresme comarca of Catalonia, Spain.
-
B.
Benicàssim
Benicàssim is a coastal town in eastern Spain best known for its Mediterranean beaches and the annual Festival Internacional de Benicàssim (FIB) music festival.
-
C.
Vilafranca del Penedès
Vilafranca del Penedès is a historic town in Catalonia, Spain, known as a traditional wine-producing center in the Penedès region.
-
D.
Banyoles
Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
-
E.
Benicarló
Benicarló is a coastal town in the province of Castellón, Spain, known for its Mediterranean beaches, agricultural production (especially artichokes), and historic old quarter.
- 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: Caldes de Montbui Triple: [Vallès Oriental, contains, Caldes de Montbui]
Generated description
Caldes de Montbui is a historic spa town in Catalonia, Spain, renowned for its thermal springs and Roman-era heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caldes de Montbui Target entity description: Caldes de Montbui is a historic spa town in Catalonia, Spain, renowned for its thermal springs and Roman-era heritage.
-
A.
Calella
Calella is a coastal town and popular tourist destination on the Mediterranean in the Maresme comarca of Catalonia, Spain.
-
B.
Benicàssim
Benicàssim is a coastal town in eastern Spain best known for its Mediterranean beaches and the annual Festival Internacional de Benicàssim (FIB) music festival.
-
C.
Vilafranca del Penedès
Vilafranca del Penedès is a historic town in Catalonia, Spain, known as a traditional wine-producing center in the Penedès region.
-
D.
Banyoles
Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
-
E.
Benicarló
Benicarló is a coastal town in the province of Castellón, Spain, known for its Mediterranean beaches, agricultural production (especially artichokes), and historic old quarter.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7322f9968819098b0ad54b913bfe4 |
completed | April 9, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74602a7ec8190980e5e6a80aa1235 |
completed | May 3, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_69f7496187988190b42e51f192cd4a80 |
completed | May 3, 2026, 1:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f74a0420908190b2b4988cc4d4a20a |
completed | May 3, 2026, 1:13 p.m. |
Created at: April 8, 2026, 9:16 p.m.