Triple
T30490063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M'Lynn Eatenton |
E775832
|
entity |
| Predicate | emotionalClimaxScene |
P101513
|
FINISHED |
| Object | funeral breakdown scene |
—
|
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: funeral breakdown scene | Statement: [M'Lynn Eatenton, emotionalClimaxScene, funeral breakdown scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalClimaxScene Context triple: [M'Lynn Eatenton, emotionalClimaxScene, funeral breakdown scene]
-
A.
climacticAct
Indicates the pivotal or most intense action or event that serves as the climax within a sequence or narrative.
-
B.
dramaticClimaxInvolvement
chosen
Indicates involvement in the pivotal, most intense turning point or climax of a dramatic work or narrative.
-
C.
typeOfClimax
Indicates the specific kind or category of climax that characterizes an event, narrative, or process.
-
D.
emotionalChallenge
Indicates a situation where one entity causes or experiences significant emotional difficulty or stress in relation to another entity or circumstance.
-
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_69f22497f91c8190afa7165bc900accd |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68748a0548190a881253cf0fd001e |
completed | May 2, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:13 p.m.