Triple
T4993133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lago Ranco |
E112179
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ranco Province |
E118979
|
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: Ranco Province | Statement: [Lago Ranco, locatedIn, Ranco Province]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranco Province Context triple: [Lago Ranco, locatedIn, Ranco Province]
-
A.
Ranco Province
chosen
Ranco Province is an administrative division in southern Chile known for its lakes, rivers, and rural landscapes within the Los Ríos Region.
-
B.
Gualivá Province
Gualivá Province is an administrative subdivision of the Cundinamarca Department in central Colombia, known for its mountainous terrain and agricultural towns.
-
C.
Itata Province
Itata Province is an administrative division in Chile's Ñuble Region, known for its rural landscapes, wine production, and small provincial capital of Quirihue.
-
D.
Caranavi Province
Caranavi Province is an administrative province in Bolivia known for its coffee production and location within the Yungas region of the La Paz Department.
-
E.
Orellana Province
Orellana Province is an Amazonian region in northeastern Ecuador known for its vast tropical rainforests, rich biodiversity, and significant oil reserves.
- 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_69bd4432b32c81909f3b3c6bd10f0653 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd729d3d448190a414a003a75104f6 |
completed | March 20, 2026, 4:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf10b0ec0c8190bcd4503dd09667c7 |
completed | March 21, 2026, 9:42 p.m. |
Created at: March 20, 2026, 1:34 p.m.