Triple
T1964186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauron (voice and motion capture) |
E42650
|
entity |
| Predicate | portrayalMethod |
P9800
|
FINISHED |
| Object | voice acting |
—
|
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: voice acting | Statement: [Sauron (voice and motion capture), portrayalMethod, voice acting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalMethod Context triple: [Sauron (voice and motion capture), portrayalMethod, voice acting]
-
A.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
B.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
C.
depictionType
chosen
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
portrayedByWork
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular entity.
-
E.
portraysGroup
Indicates that one entity depicts, represents, or visually illustrates a group of entities as its subject.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.