Triple
T32192449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talky Tina doll |
E822292
|
entity |
| Predicate | formatOfCharacter |
P80112
|
FINISHED |
| Object | prop doll with voice performance |
—
|
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: prop doll with voice performance | Statement: [Talky Tina doll, formatOfCharacter, prop doll with voice performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formatOfCharacter Context triple: [Talky Tina doll, formatOfCharacter, prop doll with voice performance]
-
A.
characterForm
Indicates that one entity is a particular form, version, or transformation state of a character.
-
B.
formatCharacteristics
Indicates how something is structured, arranged, or presented in terms of its format or layout.
-
C.
styleCharacter
Indicates that one entity defines, influences, or characterizes the stylistic qualities or manner of expression of another entity.
-
D.
characterRepresentation
Indicates a relationship where one entity serves as the symbolic, visual, or conceptual depiction of another entity’s character or identity.
-
E.
portrayalFormat
chosen
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 12:35 a.m.