Triple

T33405124
Position Surface form Disambiguated ID Type / Status
Subject Luther, Obama’s Anger Translator E855416 entity
Predicate relationshipToObamaCharacter P38921 FINISHED
Object serves as emotional interpreter 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: serves as emotional interpreter | Statement: [Luther, Obama’s Anger Translator, relationshipToObamaCharacter, serves as emotional interpreter]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipToObamaCharacter
Context triple: [Luther, Obama’s Anger Translator, relationshipToObamaCharacter, serves as emotional interpreter]
  • A. termRelationToPresident
    Indicates the nature of a person’s connection or role in relation to a president, such as their position, association, or involvement with that president.
  • B. relationshipToTruman
    Indicates the specific familial, social, or professional connection that an entity has with Truman.
  • C. relationshipToHomer
    Indicates the specific familial or social relationship that one entity has to Homer.
  • D. relationshipToCharacter chosen
    Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
  • E. relationshipToWalterSobchak
    Indicates the specific personal or social relationship that one entity has to Walter Sobchak.
  • 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_69f3496f04a08190804e56ac5098b8e4 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a037c8ae0248190b7e2ce4bf852c22d completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379f505c88190ac0879ab422c3054 completed May 12, 2026, 7:05 p.m.
Created at: May 1, 2026, 1:36 a.m.