Triple

T23664572
Position Surface form Disambiguated ID Type / Status
Subject Kirishima Shrine E584540 entity
Predicate hasCategory P87 FINISHED
Object Kokuhei Chūsha
Kokuhei Chūsha was a historical rank in the modern system of Shinto shrine classification, designating mid-level government-supported national shrines during the Meiji period in Japan.
E1596324 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: Kokuhei Chūsha | Statement: [Kirishima Shrine, hasCategory, Kokuhei Chūsha]
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: Kokuhei Chūsha
Triple: [Kirishima Shrine, hasCategory, Kokuhei Chūsha]
Generated description
Kokuhei Chūsha was a historical rank in the modern system of Shinto shrine classification, designating mid-level government-supported national shrines during the Meiji period in Japan.

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_69e24901421881908c17a5293bdd4a8e completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b40ad45c8190a3a0ae7c7f9bf3a5 completed April 29, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45b67ed481909e7537c4cdd31724 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f47336054819084117d5f59c7b7df completed May 21, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0f48696d40819093e5fbeffa0b8925 completed May 21, 2026, 6:01 p.m.
Created at: April 17, 2026, 6:50 p.m.