Triple
T16361461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penedono |
E397320
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Tabuaço |
E397314
|
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: Tabuaço | Statement: [Penedono, borderedBy, Tabuaço]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabuaço Context triple: [Penedono, borderedBy, Tabuaço]
-
A.
Tabuaço
chosen
Tabuaço is a Portuguese municipality in the Douro region, known for its terraced vineyards and production of Port and Douro wines.
-
B.
Tabuelan
Tabuelan is a coastal municipality in the province of Cebu in the Philippines, known for its beaches and rural, laid-back atmosphere.
-
C.
Tábua
Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
-
D.
Tabulam
Tabulam is a small rural village in northern New South Wales, Australia, situated on the Clarence River and known for its historic bridge and surrounding farming country.
-
E.
Tabulahan
Tabulahan is a dialect of the Aralle-Tabulahan language spoken by a local community in West Sulawesi, Indonesia.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad304448190b3f6f0350a1e151d |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dbeabe081909e3d02676293e8b2 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:08 a.m.