Triple
T10644947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osona |
E250812
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Centelles
Centelles is a municipality in the comarca of Osona in Catalonia, Spain, known for its historic center and traditional festivals.
|
E878098
|
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: Centelles | Statement: [Osona, contains, Centelles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Centelles Context triple: [Osona, contains, Centelles]
-
A.
Diéguez
Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
-
B.
Calvero
Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Negrete
Negrete is a small town and commune in Chile’s Biobío Region, known for its rural character and location near the Biobío River.
-
E.
Argüelles
Argüelles is a Madrid Metro station serving the Argüelles neighborhood, providing an interchange between several central metro lines.
- 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: Centelles Triple: [Osona, contains, Centelles]
Generated description
Centelles is a municipality in the comarca of Osona in Catalonia, Spain, known for its historic center and traditional festivals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Centelles Target entity description: Centelles is a municipality in the comarca of Osona in Catalonia, Spain, known for its historic center and traditional festivals.
-
A.
Diéguez
Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
-
B.
Calvero
Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Negrete
Negrete is a small town and commune in Chile’s Biobío Region, known for its rural character and location near the Biobío River.
-
E.
Argüelles
Argüelles is a Madrid Metro station serving the Argüelles neighborhood, providing an interchange between several central metro lines.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfd04ca88190ac4fffd13c1f33a8 |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a580d388190aea5edadd4afc0d1 |
completed | April 10, 2026, 10:31 p.m. |
| NEDg | Description generation | batch_69d97cc20448819094d650b9c1067dca |
completed | April 10, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d97e0cda0c8190af5013b971b2ad3c |
completed | April 10, 2026, 10:47 p.m. |
Created at: April 8, 2026, 9:05 p.m.