Triple

T17460516
Position Surface form Disambiguated ID Type / Status
Subject Naha City Hall E425138 entity
Predicate hasOfficialScripts P4434 FINISHED
Object Japanese 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: Japanese writing system | Statement: [Naha City Hall, hasOfficialScripts, Japanese writing system]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOfficialScripts
Context triple: [Naha City Hall, hasOfficialScripts, Japanese writing system]
  • A. hasNotableScript
    Indicates that an entity is associated with a script (such as a writing system or screenplay) that is considered notable or significant.
  • B. officialScriptOf chosen
    Indicates that one writing system is formally designated as the standard or legally recognized script used for a particular language, region, or entity.
  • C. notOfficialScriptFor
    Indicates that a given writing system is explicitly not recognized or used as the official script for a particular language or entity.
  • D. hasOfficial
    Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
  • E. hasScriptedNature
    Indicates that something is predetermined or follows a written or planned script rather than occurring spontaneously.
  • 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451a3031c8190ab1dd0d41b002dd2 completed April 19, 2026, 3:53 a.m.
PD Predicate disambiguation batch_69e3b4f0e3fc819094e466b74622c956 completed April 18, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:47 a.m.