Triple

T32468601
Position Surface form Disambiguated ID Type / Status
Subject Hakkoda Maru Memorial Ship E829782 entity
Predicate operator P179 FINISHED
Object Seikan Ferry
Seikan Ferry was a Japanese ferry operator that ran passenger and vehicle services across the Tsugaru Strait between Honshu and Hokkaido before the opening of the Seikan Tunnel.
E2012698 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: Seikan Ferry | Statement: [Hakkoda Maru Memorial Ship, operator, Seikan Ferry]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Seikan Ferry
Triple: [Hakkoda Maru Memorial Ship, operator, Seikan Ferry]
Generated description
Seikan Ferry was a Japanese ferry operator that ran passenger and vehicle services across the Tsugaru Strait between Honshu and Hokkaido before the opening of the Seikan Tunnel.

Provenance (5 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_69f3491ee87c81908cbf5890079c2af6 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c35400148190952f711f098ae7a3 completed May 3, 2026, 3:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347b7276a48190af8d88867d130a3f completed June 18, 2026, 11:12 p.m.
NEDg Description generation batch_6a347cb4b3848190badc3f8bf4d184e8 completed June 18, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_6a347da3535081908263b33d3a3045fa completed June 18, 2026, 11:22 p.m.
Created at: May 1, 2026, 12:57 a.m.