Triple

T10044719
Position Surface form Disambiguated ID Type / Status
Subject Hawamim surahs E207585 entity
Predicate haveLinguisticFeature P7162 FINISHED
Object strong rhetorical style 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: strong rhetorical style | Statement: [Hawamim surahs, haveLinguisticFeature, strong rhetorical style]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveLinguisticFeature
Context triple: [Hawamim surahs, haveLinguisticFeature, strong rhetorical style]
  • A. hasLinguisticFeature chosen
    Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
  • B. linguisticFeature
    Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
  • C. hasVerbalFeature
    Indicates that an entity possesses a specific verbal property, characteristic, or behavior related to speech or language.
  • D. linguisticFeatureStatus
    Indicates the current condition or state of a particular linguistic feature (such as whether it is present, active, obsolete, or otherwise characterized) in relation to an entity.
  • E. hasLinguisticElement
    Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
  • 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf62ecf081909c055171b78a883a completed April 2, 2026, 2:07 a.m.
PD Predicate disambiguation batch_69cd4b8d2280819089de27e57babd1f3 completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 8:56 p.m.