Triple

T35074814
Position Surface form Disambiguated ID Type / Status
Subject 佐賀県 E1011980 entity
Predicate hasExpressway P385 FINISHED
Object 長崎自動車道
長崎自動車道は、九州北部の佐賀県と長崎県を結び、長崎方面への主要な高速道路アクセスを担う高速自動車国道である。
 E2123974 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: 長崎自動車道 | Statement: [佐賀県, hasExpressway, 長崎自動車道]
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: 長崎自動車道
Triple: [佐賀県, hasExpressway, 長崎自動車道]
Generated description
長崎自動車道は、九州北部の佐賀県と長崎県を結び、長崎方面への主要な高速道路アクセスを担う高速自動車国道である。

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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7865a08408190af85d3620b509e67 completed May 3, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c646b83c819093212ae8495507c0 completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c6ea4f688190bfc3c69da98aefe4 completed June 21, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_6a37c7e9f2e4819081f46285fb314fa4 completed June 21, 2026, 11:15 a.m.
Created at: May 3, 2026, 4:01 p.m.