Triple

T1883209
Position Surface form Disambiguated ID Type / Status
Subject Marie-Louise E39898 entity
Predicate associatedWithHistoricalFigures P26467 FINISHED
Object yes 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: yes | Statement: [Marie-Louise, associatedWithHistoricalFigures, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithHistoricalFigures
Context triple: [Marie-Louise, associatedWithHistoricalFigures, yes]
  • A. historicalFigure
    Indicates that an entity is recognized as a notable person from the past who played a significant role in history.
  • B. historicalFigureAssociated chosen
    Indicates that there is a notable connection or linkage between an entity and a historical figure, such as influence, collaboration, representation, or involvement in the figure’s life or legacy.
  • C. historicalFigureDiscussed
    Indicates that a historical figure is the topic of discussion, analysis, or commentary in some context.
  • D. historicalReference
    Indicates that one entity refers to, cites, or alludes to another entity from an earlier time or historical context.
  • E. hasHistoricalWritingInfluenceFrom
    Indicates that one entity’s historical writing style, content, or traditions are influenced by those of another entity.
  • 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb4f53f408190ae30e1a12721e7d7 completed March 7, 2026, 5:17 a.m.
PD Predicate disambiguation batch_69abafe497a88190a1da6af2888b71b4 completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:34 p.m.