Triple
T1210451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergipe |
E25986
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Estância |
E155173
|
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: Estância | Statement: [Sergipe, hasMunicipality, Estância]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Estância Context triple: [Sergipe, hasMunicipality, Estância]
-
A.
Estância
chosen
Estância is a municipality in the Brazilian state of Sergipe, known for its coastal location and traditional June festivals.
-
B.
Tocancipá
Tocancipá is a Colombian municipality in the department of Cundinamarca, known for its industrial activity, motorsport circuit, and proximity to Bogotá.
-
C.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
-
D.
Chañaral
Chañaral is a coastal city in northern Chile known historically for its mining activity and its location along the Atacama Desert shoreline.
-
E.
Panguipulli
Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde4670481908c16a3a8c1a54aad |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd46eefa48190baebc12fdf916941 |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:46 p.m.