Triple
T1787963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Oyelowo as Martin Luther King Jr. |
E39430
|
entity |
| Predicate | portrayalPreparation |
P2534
|
FINISHED |
| Object | research on Martin Luther King Jr. |
—
|
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: research on Martin Luther King Jr. | Statement: [David Oyelowo as Martin Luther King Jr., portrayalPreparation, research on Martin Luther King Jr.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalPreparation Context triple: [David Oyelowo as Martin Luther King Jr., portrayalPreparation, research on Martin Luther King Jr.]
-
A.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
B.
preparesFor
chosen
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
-
C.
portrayedByWork
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular entity.
-
D.
challengesPortrayalOf
Indicates that one entity questions, disputes, or undermines the way another entity is represented or depicted.
-
E.
portraitSpecialization
Indicates that one entity specializes in creating or working with portraits, distinguishing a focused area of expertise within a broader artistic or professional domain.
- 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.