Triple
T26944810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy |
E678607
|
entity |
| Predicate | hasEmotionAssociation |
P82444
|
FINISHED |
| Object | happiness |
—
|
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: happiness | Statement: [Happy, hasEmotionAssociation, happiness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmotionAssociation Context triple: [Happy, hasEmotionAssociation, happiness]
-
A.
emotionAssociation
chosen
Indicates an emotional relationship or connection that one entity has toward another entity or concept.
-
B.
hasTypeOfEmotion
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
-
C.
emotionSpectrumAffiliation
Indicates an entity’s association or alignment with a particular range or category of emotions along an emotional spectrum.
-
D.
requiresEmotion
Indicates that one entity’s occurrence, validity, or performance depends on the presence or experience of a particular emotion in another entity.
-
E.
emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6247480cc8190a887eedaeb94615c |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 6:20 a.m.