Triple
T14616042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bengo Province |
E343087
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Caxito |
E1110094
|
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: Caxito | Statement: [Bengo Province, containsSettlement, Caxito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caxito Context triple: [Bengo Province, containsSettlement, Caxito]
-
A.
Caxito
chosen
Caxito is a town in northwestern Angola that serves as the administrative and economic center of Bengo Province.
-
B.
Guarijío
Guarijío is an indigenous Uto-Aztecan language spoken by the Guarijío people of northern Mexico, particularly in the states of Chihuahua and Sonora.
-
C.
Caxangá
Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
-
D.
Chacala
Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
-
E.
Sibaté
Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb46439b88190a4affcc7ccedab6b |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5cbcf08819084313bf28f0bb3e1 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:25 a.m.