Triple
T76801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oski the Bear |
E1534
|
entity |
| Predicate | characterType |
P662
|
FINISHED |
| Object | anthropomorphic bear |
—
|
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: anthropomorphic bear | Statement: [Oski the Bear, characterType, anthropomorphic bear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterType Context triple: [Oski the Bear, characterType, anthropomorphic bear]
-
A.
characterBasedOn
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
B.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
roleInTheology
Indicates the specific function, position, or significance an entity holds within a theological system, doctrine, or belief framework.
-
D.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
E.
nameType
Indicates the specific category or type of a name associated with an entity (e.g., legal name, nickname, alias, or preferred name).
- F. None of above.
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_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. |
Created at: Feb. 28, 2026, 2:06 a.m.