Triple
T22109230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castelo de Abrantes |
E546370
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Abrantes town |
—
|
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: Abrantes town | Statement: [Castelo de Abrantes, hasViewOf, Abrantes town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abrantes town Context triple: [Castelo de Abrantes, hasViewOf, Abrantes town]
-
A.
Abrantes
chosen
Abrantes is a historic Portuguese city in the Santarém District, known for its hilltop castle and strategic location overlooking the Tagus River.
-
B.
Lousã
Lousã is a town and municipality in central Portugal known for its surrounding mountains, schist villages, and outdoor activities such as hiking and mountain biking.
-
C.
Alcobaça
Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
-
D.
Aveiro
Aveiro is a coastal city in central Portugal known for its picturesque canals, colorful moliceiro boats, and distinctive Art Nouveau architecture.
-
E.
Torres Novas
Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291b9c988190b3ddd06d1f40dc78 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.