Triple

T3337457
Position Surface form Disambiguated ID Type / Status
Subject Tsonga E70172 entity
Predicate linguasphereCode P15767 FINISHED
Object 99-AUT-a 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: 99-AUT-a | Statement: [Tsonga, linguasphereCode, 99-AUT-a]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: linguasphereCode
Context triple: [Tsonga, linguasphereCode, 99-AUT-a]
  • A. hasLinguasphereCode chosen
    Indicates that an entity is associated with a specific Linguasphere code that identifies its language or linguistic variety within the Linguasphere classification system.
  • B. ISO639-3CodeOfLanguage
    Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
  • C. sharesISO639-3CodeWith
    Indicates that two language entities share the same ISO 639-3 code, meaning they are treated as the same language in that coding system.
  • D. languageCodeISO639-2
    Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
  • E. ISO639CollectiveCode
    Indicates that the relationship assigns or associates an ISO 639 collective language code (a code representing a group of related languages) to the relevant language entity or set of languages.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bc31b4819085f01e0b5a7cbc5d completed March 8, 2026, 5:28 p.m.
PD Predicate disambiguation batch_69ada42c2ba8819091136805ce17b39d completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:12 p.m.