Triple
T4825759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Kong |
E107820
|
entity |
| Predicate | portrayedUsing |
P37849
|
FINISHED |
| Object | stop-motion animation |
—
|
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: stop-motion animation | Statement: [King Kong, portrayedUsing, stop-motion animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedUsing Context triple: [King Kong, portrayedUsing, stop-motion animation]
-
A.
portrayedVia
chosen
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
B.
portrayedAsFrom
Indicates that one entity is depicted or represented as originating from, or belonging to, the place or source specified by another entity.
-
C.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
D.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
E.
portrayedByWork
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.