Triple
T13878896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onyota’a:ka |
E333654
|
entity |
| Predicate | traditionalClanAnimals |
P88234
|
FINISHED |
| Object | Bear |
E241117
|
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: Bear | Statement: [Onyota’a:ka, traditionalClanAnimals, Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bear Context triple: [Onyota’a:ka, traditionalClanAnimals, Bear]
-
A.
Bear
"Bear" is the NATO reporting name for the Tupolev Tu-95, a long-range, turboprop-powered strategic bomber and maritime patrol aircraft developed by the Soviet Union.
-
B.
bear
chosen
A bear is a large, typically omnivorous mammal known for its powerful build, thick fur, and presence in diverse habitats across the Northern Hemisphere and parts of the Southern Hemisphere.
-
C.
Beary
Beary is a Dravidian language spoken primarily by the Beary Muslim community in the coastal districts of Karnataka, India.
-
D.
Bruiser the Bear
Bruiser the Bear is the costumed bear mascot who represents Baylor University’s athletic teams and school spirit.
-
E.
Badger
Badger is a fictional character appearing in the work "The Return of Ulysses."
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa428ac819084e7c4b244d15f20 |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c7100b308190bdd5feaa116ee5fe |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:15 p.m.