Triple

T6399866
Position Surface form Disambiguated ID Type / Status
Subject The Protagonist E144033 entity
Predicate relationshipWithKat Barton P70419 FINISHED
Object protective ally 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: protective ally | Statement: [The Protagonist, relationshipWithKat Barton, protective ally]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipWithKat Barton
Context triple: [The Protagonist, relationshipWithKat Barton, protective ally]
  • A. relationshipToKateKeller
    Indicates the specific familial, social, or interpersonal connection that one entity has to Kate Keller.
  • B. relationshipToCatherine
    Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
  • C. hasPoliticalRelationshipWith
    Indicates a political connection or association between two entities, such as alliances, rivalries, collaborations, or other forms of political interaction.
  • D. relationshipToHannah
    Indicates the specific type of relationship or connection that an entity has to Hannah.
  • E. relationshipToParliament
    Indicates the nature or type of formal connection an entity has with a parliament, such as its role, status, or institutional relationship to that legislative body.
  • F. None of above. chosen

Provenance (4 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068994354819086cd51b661137f5a completed March 22, 2026, 10:09 p.m.
PD Predicate disambiguation batch_69c060f25c088190b433f78553ff1d84 completed March 22, 2026, 9:36 p.m.
PDg Predicate description generation batch_69c0623d23448190a75cf5d802fc0a02 completed March 22, 2026, 9:42 p.m.
Created at: March 22, 2026, 4:35 p.m.