Triple

T13265392
Position Surface form Disambiguated ID Type / Status
Subject Kashiwa E315909 entity
Predicate hasRailwayStation P918 FINISHED
Object Kita-Kashiwa Station
Kita-Kashiwa Station is a railway station in Kashiwa, Chiba Prefecture, Japan, serving as a local stop on the busy Jōban Line operated by East Japan Railway Company (JR East).
E1948156 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: Kita-Kashiwa Station | Statement: [Kashiwa, hasRailwayStation, Kita-Kashiwa Station]
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: Kita-Kashiwa Station
Triple: [Kashiwa, hasRailwayStation, Kita-Kashiwa Station]
Generated description
Kita-Kashiwa Station is a railway station in Kashiwa, Chiba Prefecture, Japan, serving as a local stop on the busy Jōban Line operated by East Japan Railway Company (JR East).

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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901c65048190bd8b3c4872f22520 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2946f68fbc8190af165752f6661ea9 completed June 10, 2026, 11:13 a.m.
NEDg Description generation batch_6a29476db6948190a440b0f297af592c completed June 10, 2026, 11:15 a.m.
NED2 Entity disambiguation (via description) batch_6a294892e7c081908d287621ab97a8b9 completed June 10, 2026, 11:20 a.m.
Created at: April 9, 2026, 9:25 p.m.