Triple

T35883670
Position Surface form Disambiguated ID Type / Status
Subject Al-Taysir E1037578 entity
Predicate clarityOfStyle P173939 FINISHED
Object clear and practical format 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: clear and practical format | Statement: [Al-Taysir, clarityOfStyle, clear and practical format]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: clarityOfStyle
Context triple: [Al-Taysir, clarityOfStyle, clear and practical format]
  • A. stylisticQuality chosen
    Indicates the relationship in which one entity characterizes or evaluates the manner, style, or expressive quality of another entity or work.
  • B. stylisticUniqueness
    Indicates that one entity possesses a distinctive style or manner that sets it apart from others.
  • C. rhetoricalStyle
    Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
  • D. stylisticFocus
    Indicates a relationship where something is primarily concerned with, emphasizes, or is characterized by a particular style or set of stylistic features.
  • E. stylisticSignificance
    Indicates that one entity holds importance or meaning specifically because of its style or manner of expression in relation to another entity or context.
  • 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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa3883d48190b05e3d2da7a017ae completed May 3, 2026, 8:04 p.m.
PD Predicate disambiguation batch_69f7a8d435288190b30b1991fb003121 completed May 3, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:06 p.m.