Triple
T5486843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribatejo |
E123602
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Torres Novas |
E436183
|
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: Torres Novas | Statement: [Ribatejo, hasCity, Torres Novas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torres Novas Context triple: [Ribatejo, hasCity, Torres Novas]
-
A.
Torres Novas
chosen
Torres Novas is a historic Portuguese city known for its medieval castle and location in the Santarém District of central Portugal.
-
B.
Lamego
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.
-
C.
Carcavelos
Carcavelos is a coastal town in the Lisbon metropolitan area of Portugal, known for its popular sandy beach and strong surfing conditions along the Estoril coastline.
-
D.
Lourinhã
Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
-
E.
Alcobaça
Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd92639b3481908845c280d334117f |
completed | March 20, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c107a4786881908a5fdd26e65e949b |
completed | March 23, 2026, 9:28 a.m. |
Created at: March 20, 2026, 2:10 p.m.