Triple
T6504864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ubajara National Park |
E149982
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Ubajara |
E582449
|
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: Ubajara | Statement: [Ubajara National Park, nearestCity, Ubajara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ubajara Context triple: [Ubajara National Park, nearestCity, Ubajara]
-
A.
Ubajara
chosen
Ubajara is a small Brazilian municipality in the state of Ceará, known for its location in the Serra da Ibiapaba highlands and for the nearby Ubajara National Park with its caves and waterfalls.
-
B.
Numata
Numata is a city in Gunma Prefecture, Japan, known as a gateway to the Mount Akagi and Oze National Park areas.
-
C.
Yabu
Yabu is a small city in northern Hyōgo Prefecture, Japan, known for its rural landscapes, hot springs, and access to mountainous outdoor recreation.
-
D.
Nakawa
Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
-
E.
Ibura
Ibura is a populous residential neighborhood and district located in the southern zone of Recife, Brazil.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69965c8448190b9eb0c50711dd44f |
completed | March 27, 2026, 2:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d50b15f081909bb7024fa57d528b |
completed | March 27, 2026, 7:05 p.m. |
Created at: March 27, 2026, 1:42 p.m.