Triple
T8842531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fly (1986 film score) |
E210420
|
entity |
| Predicate | hasInfluenceOnMood |
P52747
|
FINISHED |
| Object | suspenseful atmosphere |
—
|
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: suspenseful atmosphere | Statement: [The Fly (1986 film score), hasInfluenceOnMood, suspenseful atmosphere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceOnMood Context triple: [The Fly (1986 film score), hasInfluenceOnMood, suspenseful atmosphere]
-
A.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
B.
emotionEffect
chosen
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
C.
depictsMood
Indicates that one entity visually represents or conveys the emotional state or mood of another entity.
-
D.
featuresMood
Indicates that something includes, presents, or conveys a particular mood or emotional atmosphere.
-
E.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc608946cc8190bed3c340ba303b9c |
completed | April 1, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69cc5c25b874819084c9ba391703e066 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:48 p.m.