Triple

T9414774
Position Surface form Disambiguated ID Type / Status
Subject Wakayama urban area E226988 entity
Predicate nearBodyOfWater P1489 FINISHED
Object Kii Channel E50977 NE 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: Kii Channel | Statement: [Wakayama urban area, nearBodyOfWater, Kii Channel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kii Channel
Context triple: [Wakayama urban area, nearBodyOfWater, Kii Channel]
  • A. Kii Channel chosen
    The Kii Channel is a strait in western Japan that separates the islands of Honshu and Shikoku and links the Seto Inland Sea with the Pacific Ocean.
  • B. CloudKit
    CloudKit is Apple’s cloud storage and data synchronization framework that enables developers to seamlessly store, manage, and sync app data across users’ iCloud accounts and devices.
  • C. Xumo
    Xumo is a free, ad-supported streaming television service offering a variety of live and on-demand channels and content.
  • D. Ximian
    Ximian was a software company best known for developing and supporting GNOME-based desktop and productivity applications for Linux and Unix systems.
  • E. AVOS Systems
    AVOS Systems was a technology company co-founded by YouTube’s creators that focused on developing and managing online consumer web services and social bookmarking platforms.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd68c7bd648190b17f082883c98239 completed April 1, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107b63cf48190a072e3434a7b85a8 completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:47 p.m.