Triple

T24122120
Position Surface form Disambiguated ID Type / Status
Subject Kesennuma City E597688 entity
Predicate hasTransport P1298 FINISHED
Object Kesennuma Line
The Kesennuma Line is a regional railway line in northeastern Japan that connects coastal communities in Miyagi Prefecture and was heavily affected by the 2011 Tōhoku earthquake and tsunami.
E2285268 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: Kesennuma Line | Statement: [Kesennuma City, hasTransport, Kesennuma 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: Kesennuma Line
Triple: [Kesennuma City, hasTransport, Kesennuma Line]
Generated description
The Kesennuma Line is a regional railway line in northeastern Japan that connects coastal communities in Miyagi Prefecture and was heavily affected by the 2011 Tōhoku earthquake and tsunami.

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_69e288c74200819098ab875b592cb39f completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dee47d5481909d61b8d948a24aa8 completed April 29, 2026, 10:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a45cf688c088190801df740f369e0ec completed July 2, 2026, 2:39 a.m.
NEDg Description generation batch_6a45d04d8f448190b3b27934171abec7 completed July 2, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_6a45d0afa7bc81908a95dedcf187f741 completed July 2, 2026, 2:45 a.m.
Created at: April 17, 2026, 11:05 p.m.