Triple
T662395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paws |
E11783
|
entity |
| Predicate | appearanceType |
P311
|
FINISHED |
| Object | anthropomorphic mascot |
—
|
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 mascot | Statement: [Paws, appearanceType, anthropomorphic mascot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearanceType Context triple: [Paws, appearanceType, anthropomorphic mascot]
-
A.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
B.
adaptationAppearance
Indicates that one entity appears or is depicted in an adaptation of another entity (such as a work being represented in a derived or reinterpreted version).
-
C.
displayType
Indicates the manner or format in which something is presented, shown, or rendered.
-
D.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
E.
costumeType
Indicates the specific kind or category of costume associated with an entity.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd081e8819097f289961f5eff29 |
completed | March 1, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69a49d153a948190b3ccdc331ed33617 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.