Triple
T8661578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniela Melchior |
E205559
|
entity |
| Predicate | actedIn |
P1668
|
FINISHED |
| Object | Nazaré |
E374148
|
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: Nazaré | Statement: [Daniela Melchior, actedIn, Nazaré]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nazaré Context triple: [Daniela Melchior, actedIn, Nazaré]
-
A.
Nazaré
chosen
Nazaré is a Portuguese coastal town famous for its massive Atlantic waves and big-wave surfing.
-
B.
Cascais Bay
Cascais Bay is a scenic coastal inlet on Portugal’s Atlantic coast, known for its sandy beaches, marina, and role as a popular seaside destination near Lisbon.
-
C.
Costa da Caparica
Costa da Caparica is a coastal town and popular beach destination just south of Lisbon, Portugal, known for its long sandy shoreline and Atlantic surf.
-
D.
Sertã
Sertã is a municipality and town in central Portugal known for its forested landscapes, river beaches, and traditional cuisine.
-
E.
Beira-Mar
Beira-Mar is a Portuguese football club based in Aveiro, known for competing in the country’s professional leagues and developing notable players such as Eusébio.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc487147248190b5f1bff836a11e68 |
completed | March 31, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccfda1dc8190a3b93b1c7e813f33 |
completed | April 2, 2026, 8:09 p.m. |
Created at: March 30, 2026, 6:30 p.m.