Triple

T36463705
Position Surface form Disambiguated ID Type / Status
Subject Paiśācī E898368 entity
Predicate grammaticalDescriptionStatus P59173 FINISHED
Object fragmentary 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: fragmentary | Statement: [Paiśācī, grammaticalDescriptionStatus, fragmentary]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: grammaticalDescriptionStatus
Context triple: [Paiśācī, grammaticalDescriptionStatus, fragmentary]
  • A. grammaticalDescription chosen
    Indicates that one entity provides a description or explanation of the grammatical properties or structure of another entity.
  • B. hasGrammarStatus
    Indicates that an entity is associated with a particular grammatical status or classification (e.g., tense, mood, aspect, or correctness).
  • C. 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.
  • D. hasPhonologicalDescriptionStatus
    Indicates that there exists a specified status or condition associated with the phonological description of an entity.
  • E. hasGrammarFullyDescribed
    Indicates that the complete grammar of an entity (such as a language or formal system) has been fully specified and documented.
  • 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_69f76e58ebd88190b75d9b169b59d793 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7be9d07ac8190adf796cbef60daf6 completed May 3, 2026, 9:31 p.m.
PD Predicate disambiguation batch_69f7bccf05bc8190b61fdb2b2a315811 completed May 3, 2026, 9:23 p.m.
Created at: May 3, 2026, 4:10 p.m.