Triple
T24582322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kill Bill film series |
E608285
|
entity |
| Predicate | featuresNarrativeTheme |
P76867
|
FINISHED |
| Object | revenge |
—
|
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: revenge | Statement: [Kill Bill film series, featuresNarrativeTheme, revenge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresNarrativeTheme Context triple: [Kill Bill film series, featuresNarrativeTheme, revenge]
-
A.
featuresThemeBy
Indicates that something (such as a work, event, or product) prominently includes or centers around a particular theme created or defined by a specified source or entity.
-
B.
featuresThemeType
Indicates that something (such as a work, event, or item) has or is characterized by a particular type of theme.
-
C.
themeCharacteristic
Indicates that a characteristic, quality, or property is attributed to or associated with a particular theme.
-
D.
narrativeMotif
Indicates a recurring thematic element, pattern, or situation that appears across one or more narratives and helps structure or convey their underlying meanings.
-
E.
narrativeThemeInvolvement
chosen
Indicates that an entity participates in or contributes to a particular narrative theme within a story or discourse.
- 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a983a4408190acdf29ccd52be9d4 |
completed | April 30, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:29 a.m.