Triple
T6305520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oruro Department |
E141365
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Oruro |
E39084
|
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: Oruro | Statement: [Oruro Department, capital, Oruro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oruro Context triple: [Oruro Department, capital, Oruro]
-
A.
Oruro
chosen
Oruro is a city in western Bolivia best known for its rich mining history and its UNESCO-recognized Carnival, one of South America's most famous folkloric festivals.
-
B.
Caranavi
Caranavi is a Bolivian town known as a key coffee-growing and agricultural hub in the Yungas region.
-
C.
Saña
Saña is a historic town in northern Peru known for its colonial heritage and association with early Spanish ecclesiastical figures.
-
D.
Chepica
Chepica is a small town and commune in central Chile’s O’Higgins Region, known for its agricultural activity and role within the Colchagua Valley wine area.
-
E.
Candelaria
Candelaria is a municipality in western Cuba known for its agricultural activities and rural communities within Artemisa Province.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06479acec819090306a155a03b774 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e44527488190b3d605e917c8dfb2 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:28 p.m.