Triple

T1199610
Position Surface form Disambiguated ID Type / Status
Subject Remote Oceanic languages E25748 entity
Predicate haveWritingSystem P454 FINISHED
Object Latin script (for many languages) 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: Latin script (for many languages) | Statement: [Remote Oceanic languages, haveWritingSystem, Latin script (for many languages)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: haveWritingSystem
Context triple: [Remote Oceanic languages, haveWritingSystem, Latin script (for many languages)]
  • A. writingSystem chosen
    Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
  • B. isMostWidelyUsedWritingSystem
    Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
  • C. writingSystemFeatures
    Indicates the specific structural or functional characteristics that define how a particular writing system represents language.
  • D. writingSystemDevelopedFrom
    Indicates that one writing system originated, evolved, or was derived from another earlier writing system.
  • E. hasWritingTraditionSince
    Indicates that a writing tradition has been present or established for an entity starting from a specified point in time.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9d56748190a12fe4a30346f1d8 completed March 1, 2026, 10:28 p.m.
PD Predicate disambiguation batch_69a4bb5ed2b88190aab992913957e1cf completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:46 p.m.