Triple
T16361526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarouca |
E397321
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Lamego |
—
|
NE NERFINISHED |
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: Lamego | Statement: [Tarouca, locatedNear, Lamego]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lamego Context triple: [Tarouca, locatedNear, Lamego]
-
A.
Lamego
chosen
Lamego is a historic city in northern Portugal known for its baroque Sanctuary of Our Lady of Remedies and its location in the Douro wine region.
-
B.
Torres Novas
Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
-
C.
Montalegre
Montalegre is a town in northern Portugal known for its historic castle, traditional rural culture, and role as the seat of Montalegre Municipality in the Trás-os-Montes region.
-
D.
Lourinhã
Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
-
E.
Montemor-o-Velho
Montemor-o-Velho is a historic Portuguese town and municipality in central Portugal, known for its medieval castle overlooking the Mondego River and surrounding agricultural plains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad304448190b3f6f0350a1e151d |
completed | April 18, 2026, 3:30 a.m. |
Created at: April 10, 2026, 5:08 a.m.