Triple
T4138680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igreja de Santiago (Tavira) |
E89219
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tavira |
E13884
|
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: Tavira | Statement: [Igreja de Santiago (Tavira), locatedIn, Tavira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tavira Context triple: [Igreja de Santiago (Tavira), locatedIn, Tavira]
-
A.
Tavira
chosen
Tavira is a historic coastal town in Portugal’s Algarve region, known for its picturesque old town, Roman bridge, and nearby island beaches.
-
B.
Portimão
Portimão is a coastal city and popular tourist destination in southern Portugal, known for its beaches, marina, and vibrant waterfront along the Arade River.
-
C.
Silves
Silves is a historic town in southern Portugal known for its well-preserved Moorish castle and former status as the medieval capital of the Algarve region.
-
D.
Albufeira
Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
-
E.
Marina de Tavira
Marina de Tavira is a Mexican actress best known internationally for her Academy Award–nominated supporting role in Alfonso Cuarón’s film "Roma."
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02485a788190ba6ee769e663b2d3 |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d0510fcc81908e65f0ae8633db06 |
completed | March 14, 2026, 9:17 p.m. |
Created at: March 9, 2026, 3:43 p.m.