Triple
T7458974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alto Hospicio |
E176195
|
entity |
| Predicate | distanceTo |
P350
|
FINISHED |
| Object | Iquique |
E35014
|
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: Iquique | Statement: [Alto Hospicio, distanceTo, Iquique]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iquique Context triple: [Alto Hospicio, distanceTo, Iquique]
-
A.
Iquique
chosen
Iquique is a coastal city in northern Chile known for its major Pacific port, free-trade zone, and proximity to the Atacama Desert.
-
B.
Quillota
Quillota is a Chilean city known for its agricultural production and historical significance within the Valparaíso Region.
-
C.
Calama
Calama is a city in northern Chile known as a key mining center and gateway to the Atacama Desert.
-
D.
Traiguén
Traiguén is a town and commune in southern Chile’s Araucanía Region, known historically for agriculture and forestry within the Malleco area.
-
E.
Nancagua
Nancagua is a town and commune in central Chile’s Colchagua Valley, known for its agricultural activity and wine production.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d332d08190a05c92a00ed09ac6 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c834597d94819081f57de7d5ae30af |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:36 p.m.