Triple

T26799412
Position Surface form Disambiguated ID Type / Status
Subject Dean Sampson E671056 entity
Predicate hasRelationshipToCharacter P38921 FINISHED
Object friend of Zack Siler 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: friend of Zack Siler | Statement: [Dean Sampson, hasRelationshipToCharacter, friend of Zack Siler]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRelationshipToCharacter
Context triple: [Dean Sampson, hasRelationshipToCharacter, friend of Zack Siler]
  • A. relationshipToCharacter chosen
    Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
  • B. hasProtagonistRelationship
    Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
  • C. relatedCharacter
    Indicates that one character has a specified relationship or association with another character.
  • D. characterActorRelationship
    Indicates a relationship where an actor portrays or is associated with a specific character in a work.
  • E. relatedCharacterContext
    Indicates a contextual relationship between characters, such as roles, interactions, or situational connections that link them within a specific narrative or setting.
  • 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_69eeb31fbd888190a82dac5822e453bc completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69fe031bc6208190860099aef72d8dcb completed May 8, 2026, 3:36 p.m.
PD Predicate disambiguation batch_69fe014c8b388190b5d4e0cb95ee2be5 completed May 8, 2026, 3:29 p.m.
Created at: April 27, 2026, 4:21 a.m.