Triple

T13367633
Position Surface form Disambiguated ID Type / Status
Subject Abjad E318980 entity
Predicate classificationInLinguistics P10465 FINISHED
Object segmental writing system 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: segmental writing system | Statement: [Abjad, classificationInLinguistics, segmental writing system]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: classificationInLinguistics
Context triple: [Abjad, classificationInLinguistics, segmental writing system]
  • A. linguisticClassification chosen
    Indicates the relationship by which an entity is categorized according to its language or linguistic type.
  • B. linguisticClassificationNote
    Indicates a note providing additional information or commentary about how something is linguistically classified.
  • C. glottoCategory
    Indicates the linguistic classification or type (such as language family, subgroup, or category) to which a language or dialect is assigned.
  • D. linguisticType
    Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
  • E. hasNounClassSystem
    Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcd652d48190a782fd1f57f34b6a completed April 11, 2026, 11:44 p.m.
PD Predicate disambiguation batch_69d9a02c9abc8190b328e7bae747bfc5 completed April 11, 2026, 1:13 a.m.
Created at: April 9, 2026, 9:32 p.m.