Triple
T6012746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cachapoal Province |
E133873
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Rancagua |
E133872
|
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: Rancagua | Statement: [Cachapoal Province, hasMunicipality, Rancagua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rancagua Context triple: [Cachapoal Province, hasMunicipality, Rancagua]
-
A.
Rancagua
chosen
Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
-
B.
Chillán
Chillán is a historic city in central Chile known for its cultural heritage, markets, and as the birthplace of several prominent Chilean figures.
-
C.
Coquimbo
Coquimbo is a major Chilean port city known for its maritime commerce, fishing industry, and role as a gateway to the Elqui Valley in the Coquimbo Region.
-
D.
Talcahuano
Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
-
E.
Talca
Talca is a major city in central Chile known as an administrative, commercial, and agricultural hub in the Maule Valley.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f528acc8190bc6943d812460b57 |
completed | March 22, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d3a18e4819081b6f3c5a1f02b25 |
completed | March 24, 2026, 4:04 a.m. |
Created at: March 22, 2026, 4:06 p.m.