Triple
T16257280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manta Rota |
E394663
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Monte Gordo |
E89837
|
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: Monte Gordo | Statement: [Manta Rota, near, Monte Gordo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Gordo Context triple: [Manta Rota, near, Monte Gordo]
-
A.
Monte Gordo
chosen
Monte Gordo is a popular seaside resort town in Portugal’s Algarve region, known for its wide sandy beaches and tourism-focused amenities.
-
B.
Monte Toro
Monte Toro is the tallest mountain on the Spanish island of Menorca, known for its panoramic views and a sanctuary at its summit.
-
C.
Monte Soro
Monte Soro is a prominent mountain peak in northeastern Sicily, Italy, known as the highest summit of the Nebrodi mountain range.
-
D.
Monte Beragon
Monte Beragon is a charming but morally dubious playboy and love interest in the 1945 film noir "Mildred Pierce," whose relationship with the title character contributes to her downfall.
-
E.
Monte Castelo
Monte Castelo is a municipality in the state of Santa Catarina in southern Brazil, known for its rural landscape and small-town character.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2459b1624819086bf681075097235 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f8ca4508190a8ed7a9159dfb551 |
completed | May 10, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:04 a.m.