Triple
T7725839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Don't Worry, Be Happy" |
E175126
|
entity |
| Predicate | associatedWithMood |
P7863
|
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: ["Don't Worry, Be Happy", associatedWithMood, happiness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithMood Context triple: ["Don't Worry, Be Happy", associatedWithMood, happiness]
-
A.
hasMood
chosen
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
B.
associatedMOS
Indicates a relationship where one entity is linked to or paired with a specific Military Occupational Specialty (MOS) code or role.
-
C.
hasMoodCategory
Indicates that an entity is associated with a particular mood classification or emotional category.
-
D.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
E.
associatedWithVerb
Indicates that one entity is connected or linked to another through some verb-based relationship or action.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.