Triple

T28708196
Position Surface form Disambiguated ID Type / Status
Subject disruptive mood dysregulation disorder E729755 entity
Predicate mayBeTreatedWith P113308 FINISHED
Object stimulant medications 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: stimulant medications | Statement: [disruptive mood dysregulation disorder, mayBeTreatedWith, stimulant medications]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mayBeTreatedWith
Context triple: [disruptive mood dysregulation disorder, mayBeTreatedWith, stimulant medications]
  • A. treatmentIndication chosen
    Indicates that a treatment is intended to address, alleviate, or prevent a particular condition, symptom, or medical indication.
  • B. usesTreatment
    Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
  • C. treatmentType
    Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
  • D. hasCommonTreatment
    Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
  • E. treatsConditionType
    Indicates that one entity (typically a treatment, procedure, or intervention) is used to address, manage, or cure a particular type or category of 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_69f043e7d5a4819094b18aca10b1e024 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f6cee45590819086e489bfccbe4ac3 completed May 3, 2026, 4:28 a.m.
PD Predicate disambiguation batch_69f6cc1188708190b8f0f56e595e6057 completed May 3, 2026, 4:16 a.m.
Created at: April 28, 2026, 5:46 a.m.