Triple
T31430748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Run All Night (film score) |
E801789
|
entity |
| Predicate | associatedMood |
P7863
|
FINISHED |
| Object | tense |
—
|
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: tense | Statement: [Run All Night (film score), associatedMood, tense]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedMood Context triple: [Run All Night (film score), associatedMood, tense]
-
A.
emotionAssociation
Indicates an emotional relationship or connection that one entity has toward another entity or concept.
-
B.
hasMood
chosen
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
C.
associatedMOS
Indicates a relationship where one entity is linked to or paired with a specific Military Occupational Specialty (MOS) code or role.
-
D.
secondaryMood
Indicates a secondary or accompanying emotional state that exists alongside a primary mood in a given context.
-
E.
supportsMood
Indicates that one entity helps maintain, enhance, or positively influence the emotional state 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 8:57 p.m.