Triple

T8519711
Position Surface form Disambiguated ID Type / Status
Subject Norway rat E201664 entity
Predicate modelForDisease P83092 FINISHED
Object hypertension 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: hypertension | Statement: [Norway rat, modelForDisease, hypertension]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: modelForDisease
Context triple: [Norway rat, modelForDisease, hypertension]
  • A. hasTargetDisease
    Indicates that an entity (such as a treatment, study, or intervention) is directed toward, intended to affect, or primarily concerned with a specified disease.
  • B. diseaseType
    Indicates that one entity is classified as a specific type or category of disease in relation to another entity.
  • C. hasAssociatedDisease
    Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
  • D. humanDisease
    Indicates that the subject is a disease that affects humans.
  • E. targetsDiseaseVector
    Indicates that an entity is directed at, designed to affect, or intended to control a particular disease-carrying vector organism.
  • F. None of above. chosen

Provenance (4 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe627de908190b463da0f26da4ffb completed March 31, 2026, 3:20 p.m.
PD Predicate disambiguation batch_69cbd10f64b4819080859057c19e58f0 completed March 31, 2026, 1:50 p.m.
PDg Predicate description generation batch_69cbe30d453481908f897ed2b06e7534 completed March 31, 2026, 3:06 p.m.
Created at: March 30, 2026, 6:16 p.m.