Triple
T6066635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T. Kingfisher |
E135175
|
entity |
| Predicate | hasWritingStyleCharacteristic |
P35511
|
FINISHED |
| Object | dark humor |
—
|
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: dark humor | Statement: [T. Kingfisher, hasWritingStyleCharacteristic, dark humor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWritingStyleCharacteristic Context triple: [T. Kingfisher, hasWritingStyleCharacteristic, dark humor]
-
A.
characterStyle
Indicates how a character is visually or typographically presented, such as its font, weight, size, or decorative attributes.
-
B.
rhetoricalStyle
chosen
Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
-
C.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
D.
writtenWithCharacter
Indicates that something is written using a particular character or set of characters as its writing system or notation.
-
E.
hasMusicalStyleCharacteristic
Indicates that something possesses or exhibits a particular musical style as a defining characteristic.
- 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0573f17088190a728f1c290cc9d1d |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f031408190b08b2766237c5dd0 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:10 p.m.