Triple
T11276744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castelldefels |
E266955
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Sitges |
E878124
|
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: Sitges | Statement: [Castelldefels, borderedBy, Sitges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sitges Context triple: [Castelldefels, borderedBy, Sitges]
-
A.
Sitges
chosen
Sitges is a coastal town in Catalonia, Spain, known for its beaches, modernist architecture, and vibrant cultural and LGBTQ+ scenes.
-
B.
Girona
Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
-
C.
Begur
Begur is a picturesque coastal town in Catalonia, Spain, known for its medieval hilltop castle, charming old quarter, and scenic beaches along the Costa Brava.
-
D.
Buñol
Buñol is a small town in Spain’s Valencia region best known for hosting the annual La Tomatina tomato-throwing festival.
-
E.
Figueres
Figueres is a town in Catalonia, Spain, best known as the birthplace of surrealist artist Salvador Dalí and home to the Dalí Theatre-Museum.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e967ebb4819080b09ed3cec44e77 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f455f0bc8190994c57264f775f60 |
completed | April 19, 2026, 3:27 p.m. |
Created at: April 8, 2026, 9:31 p.m.