Triple

T14666868
Position Surface form Disambiguated ID Type / Status
Subject Rue Bennett E344398 entity
Predicate hasOverdose P115263 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: [Rue Bennett, hasOverdose, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOverdose
Context triple: [Rue Bennett, hasOverdose, yes]
  • A. riskOfOverdose
    Indicates a likelihood or potential that the subject will experience a drug or substance overdose, given certain conditions or factors.
  • B. hasAddictiveSubstance
    Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
  • C. associatedWithSubstance
    Indicates that one entity has a relevant connection or involvement with a particular substance, such as use, presence, exposure, or composition.
  • D. hasAddictionPotential
    Indicates that one entity (typically a substance or activity) has the capacity to cause another entity (typically a person) to develop dependence or addictive behavior toward it.
  • E. hasAddictionOrIssue
    Indicates that an entity experiences a dependency, compulsion, or problematic issue related to a substance, behavior, or condition.
  • 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54c69f8819080a37161deecfba8 completed April 14, 2026, 9:44 p.m.
PD Predicate disambiguation batch_69de6576f0208190aa94d995e797ac38 completed April 14, 2026, 4:04 p.m.
PDg Predicate description generation batch_69de716c17cc8190aeb85296abee85a7 completed April 14, 2026, 4:55 p.m.
Created at: April 10, 2026, 1:27 a.m.