Triple
T16827543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaixença |
E409059
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Canigó |
E485815
|
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: Canigó | Statement: [Renaixença, notableWork, Canigó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canigó Context triple: [Renaixença, notableWork, Canigó]
-
A.
Canigó
chosen
Canigó is a prominent mountain in the eastern Pyrenees of southern France, culturally significant to Catalan identity and often celebrated in regional literature and tradition.
-
B.
Arenys de Mar
Arenys de Mar is a coastal town and municipality in the Maresme comarca of Catalonia, Spain, known for its fishing port and Mediterranean beaches.
-
C.
Banyoles
Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
-
D.
Cap de Creus
Cap de Creus is a rugged, windswept peninsula on Spain’s Costa Brava, famed for its dramatic coastal landscapes and its association with the painter Salvador Dalí.
-
E.
Vilassar de Mar
Vilassar de Mar is a coastal town and municipality on the Mediterranean in the Maresme comarca of Catalonia, Spain, known for its beaches and residential character.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3151350819097b1c375e6df8986 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b2a0ac148190a7a7edebcb67c040 |
completed | May 10, 2026, 4:30 p.m. |
Created at: April 10, 2026, 5:23 a.m.