Triple
T36412701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cake (2014 film) |
E896922
|
entity |
| Predicate | hasSomberTone |
P170844
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cake (2014 film), hasSomberTone, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSomberTone Context triple: [Cake (2014 film), hasSomberTone, true]
-
A.
hasDarkerTone
Indicates that one entity possesses a color or shade that is visually darker than that of another entity.
-
B.
haveTone
chosen
Indicates that an entity possesses or exhibits a particular tone, such as a specific attitude, mood, or quality of expression.
-
C.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
D.
hasTonalityShift
Indicates a change in the tonal quality, mood, or key within a piece or segment, marking a shift from one tonality to another.
-
E.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd884cb2b48190b6acd473430d9e19 |
completed | May 8, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69fd8709ca208190a8bab836f0156af5 |
completed | May 8, 2026, 6:47 a.m. |
Created at: May 3, 2026, 4:10 p.m.