Triple
T31174193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother Rigby |
E794694
|
entity |
| Predicate | storyToneAssociation |
P130432
|
FINISHED |
| Object | darkly comic |
—
|
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: darkly comic | Statement: [Mother Rigby, storyToneAssociation, darkly comic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyToneAssociation Context triple: [Mother Rigby, storyToneAssociation, darkly comic]
-
A.
associatedTale
Indicates that one entity is linked or connected to a particular tale, story, or narrative.
-
B.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
C.
toneWithinFiction
Indicates the overall emotional or stylistic attitude conveyed inside a fictional work, as expressed through its narrative voice, style, or atmosphere.
-
D.
narrativeConnection
Indicates a meaningful relationship between elements within a narrative, such as events, characters, or scenes, that links them in terms of plot, causality, or thematic continuity.
-
E.
hasNarrativeToneOfWork
chosen
Indicates that a work exhibits or is characterized by a particular narrative tone.
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 29, 2026, 9:07 p.m.