Triple
T38290128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucas Dawson |
E1022334
|
entity |
| Predicate | liveActionOrVoice |
P83203
|
FINISHED |
| Object | live-action 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: live-action performance | Statement: [Lucas Dawson, liveActionOrVoice, live-action performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liveActionOrVoice Context triple: [Lucas Dawson, liveActionOrVoice, live-action performance]
-
A.
liveAction
Indicates that an entity is a live-action (non-animated) adaptation, portrayal, or version of another entity.
-
B.
liveActionCoHost
Indicates that two or more entities jointly host a live-action event, show, or production together.
-
C.
liveActionModelFor
Indicates that one entity serves as the live-action (real-world filmed) representation or counterpart of another entity, typically an animated or non-live-action version.
-
D.
dialogueAction
Indicates an action performed within a dialogue or conversation between entities, such as speaking, asking, answering, or otherwise verbally interacting.
-
E.
hasVoiceActing
chosen
Indicates that one entity provides voice performance for a character, role, or work associated with another 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_69f76df190f081908d5aa02c8a9286d0 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.