Triple
T1183339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aconcagua River |
E25189
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | La Calera |
E40577
|
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: La Calera | Statement: [Aconcagua River, flowsNear, La Calera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Calera Context triple: [Aconcagua River, flowsNear, La Calera]
-
A.
La Calera
chosen
La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
-
B.
La Serena
La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
-
C.
Junín
Junín is a central highland region of Peru known for its Andean landscapes, rich mining and agricultural activities, and historical role in Peru’s independence.
-
D.
Antofagasta de la Sierra
Antofagasta de la Sierra is a remote high-altitude town in northwestern Argentina known for its volcanic landscapes, salt flats, and Andean culture.
-
E.
Concepción
Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd35fb888190adf1e5d0615fa725 |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac93b6343c8190af6e28ccdaab6562 |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:45 p.m.