Triple

T17496003
Position Surface form Disambiguated ID Type / Status
Subject Blanquette Méthode Ancestrale E426060 entity
Predicate dosageAdded P127673 FINISHED
Object no 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: no | Statement: [Blanquette Méthode Ancestrale, dosageAdded, no]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: dosageAdded
Context triple: [Blanquette Méthode Ancestrale, dosageAdded, no]
  • A. dosageStyle
    Indicates the manner or pattern in which a dose of a substance (such as a medication) is administered or taken.
  • B. dosageStyles
    Indicates the various ways or formats in which a dosage (amount and schedule of administration) is specified or presented for a treatment or medication.
  • C. hasDoseUnit
    Indicates the unit of measurement in which a specified dose or quantity of a substance is expressed.
  • D. hasHigherDoseStrength
    Indicates that one entity has a greater dose strength than another entity in a comparative relationship.
  • E. doseAdjustmentRequiredIn
    Indicates that a change in the amount or frequency of a treatment or medication is necessary within a specified context, such as a condition, setting, or patient group.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4520e9c8c8190aa955766bc915d26 completed April 19, 2026, 3:54 a.m.
PD Predicate disambiguation batch_69e3b4f5fbcc8190a6ea9639bf5650da completed April 18, 2026, 4:44 p.m.
PDg Predicate description generation batch_69e3bbb37d148190b7f38599c06594ee completed April 18, 2026, 5:13 p.m.
Created at: April 10, 2026, 5:48 a.m.