Triple

T35625081
Position Surface form Disambiguated ID Type / Status
Subject Charles Blake E1029426 entity
Predicate intellectualMatchOf P123379 FINISHED
Object Lady Mary Crawley NE NERFINISHED

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: Lady Mary Crawley | Statement: [Charles Blake, intellectualMatchOf, Lady Mary Crawley]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: intellectualMatchOf
Context triple: [Charles Blake, intellectualMatchOf, Lady Mary Crawley]
  • A. closeIntellectualCompanion chosen
    Indicates a relationship where one entity serves as a trusted, closely engaged partner in intellectual activities, such as thinking, learning, or discussing ideas, with another entity.
  • B. intellectualRivalOf
    Indicates a relationship where two entities challenge each other’s ideas or expertise, often competing in the same intellectual domain.
  • C. hasIntellectualFocus
    Indicates that an entity’s primary attention, study, or mental effort is directed toward a particular subject, topic, or area of interest.
  • D. celebrityMatch
    Indicates a relationship where one entity is identified as a suitable or corresponding celebrity counterpart or pairing for another entity.
  • E. typeOfIntelligence
    Indicates that one entity is a specific kind or category of intelligence in relation to 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_69f76e07bb0c8190968ea2d836fc42c9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ef4a5f481909f3241a4e20ea37e completed May 3, 2026, 7:16 p.m.
PD Predicate disambiguation batch_69f79e4bdbcc8190be7a0d2cf8a77b64 completed May 3, 2026, 7:13 p.m.
Created at: May 3, 2026, 4:05 p.m.