Triple

T15884514
Position Surface form Disambiguated ID Type / Status
Subject Miyazaki Airport E385155 entity
Predicate railwayLine P848 FINISHED
Object Miyazaki Kūkō Line
The Miyazaki Kūkō Line is a short Japanese railway line in Miyazaki Prefecture that connects central Miyazaki to Miyazaki Airport, providing direct rail access for air travelers.
E1719459 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: Miyazaki Kūkō Line | Statement: [Miyazaki Airport, railwayLine, Miyazaki Kūkō Line]
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: Miyazaki Kūkō Line
Triple: [Miyazaki Airport, railwayLine, Miyazaki Kūkō Line]
Generated description
The Miyazaki Kūkō Line is a short Japanese railway line in Miyazaki Prefecture that connects central Miyazaki to Miyazaki Airport, providing direct rail access for air travelers.

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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561997bc8190a40e7d68defbbddd completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f6b6b8481908df3cb7d7ac8ca93 completed May 23, 2026, 11:28 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 10, 2026, 4:51 a.m.