Triple

T12531556
Position Surface form Disambiguated ID Type / Status
Subject Maureen E299575 entity
Predicate emotionalFunctionInWork P65521 FINISHED
Object anchors much of the film’s emotional impact 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: anchors much of the film’s emotional impact | Statement: [Maureen, emotionalFunctionInWork, anchors much of the film’s emotional impact]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: emotionalFunctionInWork
Context triple: [Maureen, emotionalFunctionInWork, anchors much of the film’s emotional impact]
  • A. moodContrastWithinWork
    Indicates a contrast or shift between different moods or emotional tones within the same work.
  • B. emotionalDynamic
    Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
  • C. emotionalCoreOf
    Indicates that one entity serves as the central source, essence, or primary driver of another entity’s emotional character or experience.
  • D. emotionalRole chosen
    Indicates a relationship where one entity holds a particular emotional significance, function, or impact in relation to another entity.
  • E. emotionalTrait
    Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95f5507b481908d13cc317b7402f6 completed April 10, 2026, 8:36 p.m.
PD Predicate disambiguation batch_69d9540d7b788190a0d57b098e90e491 completed April 10, 2026, 7:48 p.m.
Created at: April 8, 2026, 9:57 p.m.