Triple
T14033128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academia da Força Aérea |
E337641
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Pirassununga |
E270036
|
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: Pirassununga | Statement: [Academia da Força Aérea, location, Pirassununga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pirassununga Context triple: [Academia da Força Aérea, location, Pirassununga]
-
A.
Pirassununga
chosen
Pirassununga is a municipality in the state of São Paulo, Brazil, known for its agricultural activities and as a site of a major University of São Paulo campus.
-
B.
Coruripe
Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
-
C.
Panarima
Panarima is a musical track featured on the album "Legend of the Sun Virgin."
-
D.
Araricá
Araricá is a small municipality in the state of Rio Grande do Sul, Brazil, known for its rural character and integration into the Porto Alegre metropolitan region.
-
E.
Sapucaia
Sapucaia is a municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fab17008190981f1808726fa11c |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc337a5cc8190953b84255a401ada |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.