Triple
T20000301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stevie Gray |
E494302
|
entity |
| Predicate | emotionalStateInPlay |
P76175
|
FINISHED |
| Object | conflicted |
—
|
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: conflicted | Statement: [Stevie Gray, emotionalStateInPlay, conflicted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalStateInPlay Context triple: [Stevie Gray, emotionalStateInPlay, conflicted]
-
A.
emotionState
chosen
Indicates the emotional condition or feeling that an entity is currently experiencing.
-
B.
emotionDisplayed
Indicates that an entity is outwardly expressing or showing a particular emotion.
-
C.
emotionalTrait
Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
-
D.
intendedEmotion
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a15f308190a99ac3205f948acb |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e54cdddbd48190becc8b2aa5ab4ef9 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:32 p.m.