Triple
T6479863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Cup of Tea and a Slice of Cake |
E146163
|
entity |
| Predicate | hasAuthorWritingStyle |
P27486
|
FINISHED |
| Object | lighthearted |
—
|
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: lighthearted | Statement: [A Cup of Tea and a Slice of Cake, hasAuthorWritingStyle, lighthearted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorWritingStyle Context triple: [A Cup of Tea and a Slice of Cake, hasAuthorWritingStyle, lighthearted]
-
A.
authorStyle
chosen
Indicates the stylistic characteristics or manner of expression associated with a particular author in their works.
-
B.
hasAuthor
Indicates that an entity is written or created by a specific author.
-
C.
rhetoricalStyle
Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
-
D.
hasAuthorialStance
Indicates that an entity expresses, embodies, or is associated with a particular author’s viewpoint, attitude, or perspective toward its subject matter.
-
E.
probableAuthorOf
Indicates that an entity is likely, but not certainly, the author or creator of 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:51 p.m.