Triple
T3047314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ManningCast |
E83479
|
entity |
| Predicate | commentaryStyle |
P35511
|
FINISHED |
| Object | humorous |
—
|
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: humorous | Statement: [ManningCast, commentaryStyle, humorous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commentaryStyle Context triple: [ManningCast, commentaryStyle, humorous]
-
A.
commentaryOn
Indicates that one entity provides evaluative or explanatory remarks about another entity, such as a work, event, or statement.
-
B.
rhetoricalStyle
chosen
Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
-
C.
authorStyle
Indicates the stylistic characteristics or manner of expression associated with a particular author in their works.
-
D.
hasCommentaryOn
Indicates that one entity provides commentary, explanation, or evaluative remarks about another entity.
-
E.
narrativeStyle
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bad11b48190a5bd01e91a320e14 |
completed | March 8, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.