Triple
T17045092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santarém District |
E413546
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Golegã |
E379815
|
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: Golegã | Statement: [Santarém District, hasMunicipality, Golegã]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Golegã Context triple: [Santarém District, hasMunicipality, Golegã]
-
A.
Golegã
chosen
Golegã is a Portuguese town famed for its equestrian traditions and annual horse fair, located in the Centro Region of Portugal.
-
B.
Pedrógão
Pedrógão is a civil parish located within the municipality of Vidigueira in Portugal’s Alentejo region.
-
C.
Covilhã
Covilhã is a city in central Portugal, historically known for its textile industry and as a gateway to the Serra da Estrela mountain range.
-
D.
Góis
Góis is a small municipality in central Portugal known for its mountainous landscapes, river beaches, and traditional schist villages.
-
E.
Eixão
Eixão is a major central highway in Brasília, Brazil, known for its wide, high-speed lanes that run the length of the city’s main axis.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3da9d7e988190a5e3991c7123f9b0 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ed472d48190bc6aed49464dc1ff |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:33 a.m.