Triple
T141446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bess Truman |
E2858
|
entity |
| Predicate | mediaPortrayal |
P1852
|
FINISHED |
| Object | portrayed in films and television about Harry S. Truman |
—
|
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: portrayed in films and television about Harry S. Truman | Statement: [Bess Truman, mediaPortrayal, portrayed in films and television about Harry S. Truman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaPortrayal Context triple: [Bess Truman, mediaPortrayal, portrayed in films and television about Harry S. Truman]
-
A.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
B.
depictsPerson
chosen
Indicates that one entity visually represents or portrays a specific person.
-
C.
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.
-
D.
mediaCoverage
Indicates that one entity reports on, documents, or broadcasts information about another entity through news or media channels.
-
E.
usedByMedia
Indicates that something is employed or utilized by media organizations or media-related channels.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.