Triple
T15719639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seto Naikai |
E381055
|
entity |
| Predicate | connectsTo |
P845
|
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: [Seto Naikai, connectsTo, Kii Channel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kii Channel Context triple: [Seto Naikai, connectsTo, 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f932a248190b65ecfb2bc56e715 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff75852cf88190be054160d5cbc675 |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:45 a.m.