Triple
T35991022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munise |
E1040844
|
entity |
| Predicate | impactOnProtagonist |
P177018
|
FINISHED |
| Object | her death deeply affects Feride |
—
|
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: her death deeply affects Feride | Statement: [Munise, impactOnProtagonist, her death deeply affects Feride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnProtagonist Context triple: [Munise, impactOnProtagonist, her death deeply affects Feride]
-
A.
emotionalImpactOnProtagonist
chosen
Indicates how an event, action, or situation affects the protagonist’s emotional state or feelings.
-
B.
affectsCharacterArc
Indicates that one event, action, or element causes a meaningful change or development in a character’s personal journey or growth over the course of the story.
-
C.
protagonistReaction
Indicates how a main character responds emotionally or behaviorally to a particular event, situation, or stimulus.
-
D.
protagonistTransformation
Indicates a change or evolution that the main character undergoes, typically altering their traits, beliefs, or role over the course of a narrative.
-
E.
narrativeImpactOn
Indicates how one element influences, shapes, or alters the narrative significance or storyline of another.
- 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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:07 p.m.