Triple
T37246957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Dust |
E923881
|
entity |
| Predicate | moralValenceInStory |
P135865
|
FINISHED |
| Object | negative |
—
|
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: negative | Statement: [Happy Dust, moralValenceInStory, negative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralValenceInStory Context triple: [Happy Dust, moralValenceInStory, negative]
-
A.
moralTone
Indicates the evaluative moral quality or ethical character expressed in or associated with an action, statement, or situation.
-
B.
ethicalStanceInStory
Indicates the ethical position, judgment, or moral viewpoint expressed or taken within the context of a particular story or narrative.
-
C.
moralPortrayal
chosen
Indicates how an entity is depicted in terms of moral qualities, such as virtue, vice, or ethical standing, within a given context.
-
D.
moralOutcome
Indicates the moral or ethical status resulting from an action, event, or decision, such as whether it is judged right, wrong, good, or bad.
-
E.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
- 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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb9e1845e881908d19158440cf3b87 |
completed | May 6, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69fb8d08d6988190a00794ac26078348 |
completed | May 6, 2026, 6:48 p.m. |
Created at: May 3, 2026, 4:15 p.m.