Triple
T76831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oski the Bear |
E1534
|
entity |
| Predicate | hasAppearance |
P311
|
FINISHED |
| Object | large bear head with fixed smile |
—
|
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: large bear head with fixed smile | Statement: [Oski the Bear, hasAppearance, large bear head with fixed smile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAppearance Context triple: [Oski the Bear, hasAppearance, large bear head with fixed smile]
-
A.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
B.
presentedBy
Indicates that something (such as an event, performance, or work) is formally organized, hosted, or introduced by a particular person or entity.
-
C.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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.