Triple

T13131143
Position Surface form Disambiguated ID Type / Status
Subject Roman medicine E311967 entity
Predicate hasSurgicalPractice P88361 FINISHED
Object cauterization 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: cauterization | Statement: [Roman medicine, hasSurgicalPractice, cauterization]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSurgicalPractice
Context triple: [Roman medicine, hasSurgicalPractice, cauterization]
  • A. practicedMedicineIn
    Indicates that a person engaged in the professional practice of medicine within a specified location or jurisdiction.
  • B. medicalPractice
    Indicates a relationship where an entity engages in or carries out the professional provision of medical care or services.
  • C. hasSpecialty
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • D. hasPractices chosen
    Indicates that an entity engages in, follows, or carries out specific practices, methods, or customary ways of doing things.
  • E. hasPracticeFields
    Indicates that an entity possesses or is associated with one or more designated fields or areas used for practice activities.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981b27a8c81909a92ab7be5d3a7e9 completed April 10, 2026, 11:03 p.m.
PD Predicate disambiguation batch_69d98043a74c81908648e6cd0b4c7f71 completed April 10, 2026, 10:57 p.m.
Created at: April 9, 2026, 9:07 p.m.