Triple
T10902195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aguaruna |
E257472
|
entity |
| Predicate | relatedEthnicGroup |
P1969
|
FINISHED |
| Object | Huambisa |
E265767
|
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: Huambisa | Statement: [Aguaruna, relatedEthnicGroup, Huambisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huambisa Context triple: [Aguaruna, relatedEthnicGroup, Huambisa]
-
A.
Huambisa
chosen
Huambisa is an indigenous Jivaroan language spoken by the Huambisa people of the northern Peruvian Amazon.
-
B.
Chimbay
Chimbay is a town in the autonomous Republic of Karakalpakstan in northwestern Uzbekistan, serving as a local administrative and economic center in the region.
-
C.
Ouahigouya
Ouahigouya is a major city in northern Burkina Faso known as an important commercial and administrative center of the region.
-
D.
Hualañé
Hualañé is a rural Chilean town and commune in the Maule Region, known for its agricultural activities and location near the Mataquito River.
-
E.
Chacahua
Chacahua is a coastal community in Oaxaca, Mexico, known for its beaches, lagoons, and biodiversity within the Lagunas de Chacahua 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a3e83c81908dc48c0fb7935da7 |
completed | April 9, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3443f04c08190a8071ac7374115b1 |
completed | April 18, 2026, 8:43 a.m. |
Created at: April 8, 2026, 9:22 p.m.