Triple

T36748327
Position Surface form Disambiguated ID Type / Status
Subject The Second Bakery Attack E907832 entity
Predicate protagonistRelationshipStatus P104581 FINISHED
Object newlywed 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: newlywed | Statement: [The Second Bakery Attack, protagonistRelationshipStatus, newlywed]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: protagonistRelationshipStatus
Context triple: [The Second Bakery Attack, protagonistRelationshipStatus, newlywed]
  • A. protagonistFamilyStatus
    Indicates the familial role or position that a character holds in relation to the story’s protagonist.
  • B. romanticRelationshipStatus
    Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
  • C. relationshipStatusDuringFilm
    Indicates the type or state of a relationship between entities specifically during the time period in which a film takes place or is produced.
  • D. stateOfRelations
    Indicates the current nature or condition of the relationship between two or more entities, such as whether it is friendly, hostile, neutral, or otherwise characterized.
  • E. relationshipStatusInStory chosen
    Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
  • 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_69f76e76d10881909ec1679bc043108c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd6834cc8190aa27153d6a99f3bb completed May 5, 2026, 2:23 p.m.
PD Predicate disambiguation batch_69f7cf7890008190a8bc355ff2d61c86 completed May 3, 2026, 10:43 p.m.
Created at: May 3, 2026, 4:12 p.m.