Triple

T711519
Position Surface form Disambiguated ID Type / Status
Subject Milady de Winter E14216 entity
Predicate backstory P9429 FINISHED
Object was branded with a fleur-de-lis for crimes in her youth 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: was branded with a fleur-de-lis for crimes in her youth | Statement: [Milady de Winter, backstory, was branded with a fleur-de-lis for crimes in her youth]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: backstory
Context triple: [Milady de Winter, backstory, was branded with a fleur-de-lis for crimes in her youth]
  • A. storyBy
    Indicates that one entity is the creator or author of the story associated with another entity.
  • B. originStorySummary chosen
    Indicates a brief narrative explaining how something began, was created, or came into existence.
  • C. subsequentHistory
    Indicates that one event, state, or record occurs or is recorded after another in time, reflecting its later historical development or outcome.
  • D. narrativeType
    Indicates the specific kind or category of narrative (e.g., genre, structural form, or storytelling mode) associated with an entity.
  • E. backing
    Indicates providing support, endorsement, or financial/resources assistance to someone or something, often enabling or strengthening their actions or position.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a77fcc6881908a025bb21e44ad56 completed March 1, 2026, 8:54 p.m.
PD Predicate disambiguation batch_69a4a4f221b081909fbaa689fb20eb3e completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:36 p.m.