Triple

T18806118
Position Surface form Disambiguated ID Type / Status
Subject Gypsy Rose Blanchard E459877 entity
Predicate associatedMedicalCondition P129457 FINISHED
Object Munchausen syndrome by proxy (experienced as victim) 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: Munchausen syndrome by proxy (experienced as victim) | Statement: [Gypsy Rose Blanchard, associatedMedicalCondition, Munchausen syndrome by proxy (experienced as victim)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedMedicalCondition
Context triple: [Gypsy Rose Blanchard, associatedMedicalCondition, Munchausen syndrome by proxy (experienced as victim)]
  • A. clinicalCondition chosen
    Indicates that one entity has, exhibits, or is associated with a particular medical or health-related condition described by the other entity.
  • B. hasAssociatedDisease
    Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
  • C. diseaseType
    Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
  • D. mayBeComorbidWith
    Indicates that two conditions or disorders can occur together in the same individual, potentially influencing each other’s presence or severity.
  • E. diagnosedWith
    Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
  • 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a3d7f8d08190a3e02fab6dc40bb5 completed April 20, 2026, 3:56 a.m.
PD Predicate disambiguation batch_69e48d1b10ec8190985c6fb5766ff981 completed April 19, 2026, 8:06 a.m.
Created at: April 10, 2026, 11:53 a.m.