Triple
T15367484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. & Mrs. Smith (film score) |
E367454
|
entity |
| Predicate | supportsNarrativeTone |
P49759
|
FINISHED |
| Object | action |
—
|
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: action | Statement: [Mr. & Mrs. Smith (film score), supportsNarrativeTone, action]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsNarrativeTone Context triple: [Mr. & Mrs. Smith (film score), supportsNarrativeTone, action]
-
A.
supportsNarrativeOf
Indicates that one entity provides evidence, context, or structure that upholds, reinforces, or advances the storyline or interpretive account expressed by another entity.
-
B.
supportsNarrativeText
Indicates that one entity provides justification, evidence, or contextual backing that helps explain or validate the narrative content expressed by another entity.
-
C.
usesNarrativeStyle
Indicates that one entity employs or adopts a particular narrative style in presenting or structuring content or information.
-
D.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
E.
contributesToTone
chosen
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4a7cdc8190b7b48c97e774c306 |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca9ab7e88190a9261ef27be665b1 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.