Triple
T2642213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A22 |
E62894
|
entity |
| Predicate | servesCity |
P82
|
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: [A22, servesCity, Tavira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tavira Context triple: [A22, servesCity, 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.
Carvoeiro
Carvoeiro is a picturesque coastal village in southern Portugal known for its dramatic cliffs, sandy beaches, and role as a popular holiday destination.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8fdc0bc8190b7fd102b87ee50d1 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf49dc7c8190bebc1c75f6d00ef9 |
completed | March 10, 2026, 5:42 a.m. |
Created at: March 6, 2026, 9:53 p.m.