Triple

T36375757
Position Surface form Disambiguated ID Type / Status
Subject Minekaze-class destroyer E895893 entity
Predicate hasShip P14595 FINISHED
Object Japanese destroyer Yakaze
Japanese destroyer Yakaze was a Minekaze-class destroyer of the Imperial Japanese Navy that served in the interwar period and World War II, performing roles such as escort and training duties.
E2189265 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: Japanese destroyer Yakaze | Statement: [Minekaze-class destroyer, hasShip, Japanese destroyer Yakaze]
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: Japanese destroyer Yakaze
Triple: [Minekaze-class destroyer, hasShip, Japanese destroyer Yakaze]
Generated description
Japanese destroyer Yakaze was a Minekaze-class destroyer of the Imperial Japanese Navy that served in the interwar period and World War II, performing roles such as escort and training duties.

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_69f76e5115588190ad8738860b7bc68b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bb17487c819084b51886a1a1c456 completed May 3, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6c690008190972104e81a27abbb completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39ec063b0c81908b0c23c3079904eb completed June 23, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_6a39ed5773d08190b15416e6186ceaef completed June 23, 2026, 2:20 a.m.
Created at: May 3, 2026, 4:10 p.m.