Triple

T20930964
Position Surface form Disambiguated ID Type / Status
Subject Arabic mutaqārib metre E515467 entity
Predicate hasLearningMethod P16019 FINISHED
Object memorized through metrical circles and examples 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: memorized through metrical circles and examples | Statement: [Arabic mutaqārib metre, hasLearningMethod, memorized through metrical circles and examples]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLearningMethod
Context triple: [Arabic mutaqārib metre, hasLearningMethod, memorized through metrical circles and examples]
  • A. usesLearningMechanism
    Indicates that one entity employs or applies a particular learning mechanism or method in its functioning or behavior.
  • B. trainingMethod chosen
    Indicates the specific approach, technique, or procedure used to train an entity (such as a person, model, or system).
  • C. canBeLearnedBy
    Indicates that a particular subject, skill, or knowledge is capable of being acquired or mastered by a specified learner or group of learners.
  • D. learnedIn
    Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
  • E. supportsLearningMechanism
    Indicates that one entity facilitates, enables, or enhances the learning mechanism or process of another entity.
  • 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_69e0b4fb431c8190b9d40e6a72f0cc87 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f6557e4881909ce932c3f538304a completed April 21, 2026, 4 a.m.
PD Predicate disambiguation batch_69e5c9af1fe08190953366a466950140 completed April 20, 2026, 6:37 a.m.
Created at: April 16, 2026, 12:49 p.m.