Triple
T76817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oski the Bear |
E1534
|
entity |
| Predicate | universe |
P4832
|
FINISHED |
| Object | University of California, Berkeley traditions |
—
|
LITERAL 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: University of California, Berkeley traditions | Statement: [Oski the Bear, universe, University of California, Berkeley traditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: universe Context triple: [Oski the Bear, universe, University of California, Berkeley traditions]
-
A.
isOnlyKnownWorldWithLife
Indicates that the subject world is the sole world known to possess life.
-
B.
stars
Indicates that one entity marks, highlights, or designates another as special, important, or featured (often by assigning a star or similar marker).
-
C.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
-
D.
wasColonyOf
Indicates that one entity functioned as a colony under the political control or administration of another entity.
-
E.
orbits
Indicates that one object moves in a curved, usually repetitive path around another object due to a central force such as gravity.
- F. None of above. chosen
Provenance (4 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2559892dc81909303f2eefdc0025f |
completed | Feb. 28, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69a24eaf99e481908e8d314577e22ecf |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a25597b6c48190849c3e9e6351b983 |
completed | Feb. 28, 2026, 2:40 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.