Triple
T1787967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Oyelowo as Martin Luther King Jr. |
E39430
|
entity |
| Predicate | portrayalMedium |
P17824
|
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: [David Oyelowo as Martin Luther King Jr., portrayalMedium, live-action performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalMedium Context triple: [David Oyelowo as Martin Luther King Jr., portrayalMedium, live-action performance]
-
A.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of another entity.
-
B.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
C.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
D.
mediaDepictionAs
chosen
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
E.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab75457e54819096b8c6ae8c65550c |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61d165688190924962a98e07ff69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.