Triple
T25831499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gracie Allen Murder Case |
E650675
|
entity |
| Predicate | hasStoryTone |
P130432
|
FINISHED |
| Object | light-hearted |
—
|
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: light-hearted | Statement: [The Gracie Allen Murder Case, hasStoryTone, light-hearted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoryTone Context triple: [The Gracie Allen Murder Case, hasStoryTone, light-hearted]
-
A.
hasNarrativeToneOfWork
chosen
Indicates that a work exhibits or is characterized by a particular narrative tone.
-
B.
hasTenseNarrative
Indicates that a narrative is expressed using a specific grammatical tense or set of tenses.
-
C.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
D.
tellsStoriesIn
Indicates that one entity narrates or recounts stories within or to the context of another entity (such as a place, group, or medium).
-
E.
hasLiteraryTone
Indicates that something (such as a text, expression, or communication) possesses a style or manner of expression characteristic of literature or literary writing.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 22, 2026, 7:38 a.m.