Triple
T16361458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penedono |
E397320
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Sernancelhe |
—
|
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: Sernancelhe | Statement: [Penedono, borderedBy, Sernancelhe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sernancelhe Context triple: [Penedono, borderedBy, Sernancelhe]
-
A.
Sernancelhe
chosen
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
B.
Santo Tirso
Santo Tirso is a municipality in northern Portugal known for its textile industry, historic monasteries, and location in the Porto metropolitan area.
-
C.
Lourinhã
Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
-
D.
Mondim de Basto
Mondim de Basto is a small town in northern Portugal known for its scenic mountainous landscapes and role as the administrative center of the surrounding municipality.
-
E.
Penacova
Penacova is a picturesque riverside town in central Portugal known for its scenic landscapes, viewpoints, and traditional villages along the Mondego River.
- 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.