Triple
T6919932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sufiya Zinobia |
E160155
|
entity |
| Predicate | associatedWithEmotion |
P41794
|
FINISHED |
| Object | shame |
—
|
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: shame | Statement: [Sufiya Zinobia, associatedWithEmotion, shame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithEmotion Context triple: [Sufiya Zinobia, associatedWithEmotion, shame]
-
A.
emotionallyAttachedTo
Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
-
B.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
C.
intendedEmotion
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
D.
hasTypeOfEmotion
chosen
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
-
E.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9fa452c8190b2bea2d47309c889 |
completed | March 27, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:26 p.m.