Triple
T4699140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gap |
E104222
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Dénia |
E425416
|
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: Dénia | Statement: [Gap, twinTown, Dénia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dénia Context triple: [Gap, twinTown, Dénia]
-
A.
Denia
chosen
Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
-
B.
Altea
Altea is a picturesque coastal town on Spain’s Costa Blanca, known for its whitewashed old quarter, blue-domed church, and vibrant arts scene.
-
C.
Alicante
Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
-
D.
Gandia
Gandia is a coastal city in eastern Spain known for its Mediterranean beaches, historical heritage, and role as a tourist destination in the province of Valencia.
-
E.
Pietrasanta
Pietrasanta is a historic Tuscan town in Italy renowned for its marble workshops, sculpture studios, and vibrant community of international artists.
- 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_69bd43e9b88481908582103dcadff3d9 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63b57e1c8190962d97e4805974ed |
completed | March 20, 2026, 3:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03c7469081908cf587b2356a4320 |
completed | March 21, 2026, 2:34 a.m. |
Created at: March 20, 2026, 1:17 p.m.