Triple

T28075863
Position Surface form Disambiguated ID Type / Status
Subject Langya Commandery E709539 entity
Predicate administeredType P180416 FINISHED
Object counties 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: counties | Statement: [Langya Commandery, administeredType, counties]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: administeredType
Context triple: [Langya Commandery, administeredType, counties]
  • A. typeOfAdministration
    Indicates the specific form or system of administration applied to or governing an entity.
  • B. administeredWith
    Indicates that two or more treatments, drugs, or interventions are given to a patient at the same time or as part of the same therapeutic regimen.
  • C. administeredAs
    Indicates that one entity is given or applied to another entity as a treatment, dose, or intervention.
  • D. administeredFor
    Indicates that something (typically a treatment, medication, or intervention) is given or applied to an entity for a specific purpose, condition, or intended effect.
  • E. wasAdministeredAs
    Indicates that one entity (typically a treatment, drug, or intervention) was given or applied to another entity (such as a patient or subject) in a specific manner or context.
  • 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_69ef9b6f8078819098b741274cd1a2ee completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f74062b9388190b30546cf700a825c completed May 3, 2026, 12:32 p.m.
PD Predicate disambiguation batch_69f73c802b848190b61a416b7488bd96 completed May 3, 2026, 12:16 p.m.
PDg Predicate description generation batch_69f74061c440819080434155c2d60341 completed May 3, 2026, 12:32 p.m.
Created at: April 27, 2026, 8:48 p.m.