Triple
T19723078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Partzufim |
E473657
|
entity |
| Predicate | anthropomorphicAspect |
P26660
|
FINISHED |
| Object | use of human body imagery |
—
|
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: use of human body imagery | Statement: [Partzufim, anthropomorphicAspect, use of human body imagery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: anthropomorphicAspect Context triple: [Partzufim, anthropomorphicAspect, use of human body imagery]
-
A.
isAnthropomorphic
chosen
Indicates that something non-human is given human-like characteristics, form, or behavior.
-
B.
isPersonificationOf
Indicates that one entity represents or embodies an abstract concept, quality, or non-human thing in human form.
-
C.
animatedCharacter
Indicates that an entity is a fictional character depicted through animation rather than live action.
-
D.
mascotCharacteristic
Indicates that a mascot possesses or is associated with a particular characteristic or trait.
-
E.
monsterCharacteristic
Indicates that a monster possesses a particular attribute, trait, or quality.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f64984819097882c44098b1643 |
completed | April 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:46 p.m.