Triple
T5536837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moxeño |
E145182
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Moxos |
E535892
|
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: Moxos | Statement: [Moxeño, alternateName, Moxos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moxos Context triple: [Moxeño, alternateName, Moxos]
-
A.
Moxos
chosen
Moxos is a historical region in the Bolivian lowlands, known for its indigenous cultures, extensive pre-Columbian earthworks, and rich Amazonian wetlands.
-
B.
Guayaramerín
Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
-
C.
Humaitá
Humaitá is a historic town in southern Paraguay known for its strategic role and heavily fortified position during the Paraguayan War.
-
D.
Humaitá
Humaitá is a Brazilian riverside city in the state of Amazonas, known for its location along the Madeira River and its role as a regional hub in the western Amazon.
-
E.
Rurrenabaque
Rurrenabaque is a small Bolivian town known as a popular gateway to the Amazon rainforest and nearby Madidi National Park.
- 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fb07e748190bea74bbde2d7b8ba |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c059df62ac8190865dda631da4cec0 |
completed | March 22, 2026, 9:06 p.m. |
Created at: March 22, 2026, 3:34 p.m.