Triple

T25983275
Position Surface form Disambiguated ID Type / Status
Subject Duke of Kent family E646126 entity
Predicate usesSurname P14929 FINISHED
Object Windsor
Windsor is the royal house name adopted by the British monarchy and its extended family, including the Duke of Kent’s line.
E23131 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: Windsor | Statement: [Duke of Kent family, usesSurname, Windsor]
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: Windsor
Triple: [Duke of Kent family, usesSurname, Windsor]
Generated description
Windsor is the royal house name adopted by the British monarchy and its extended family, including the Duke of Kent’s line.

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_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f60511cfe88190b2b88b40fb4ec269 completed May 2, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a110772a1c08190af91a53bde823a92 completed May 23, 2026, 1:48 a.m.
NEDg Description generation batch_6a11080f37c08190b1e814533c85f8f2 completed May 23, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_6a1108aa194481908986a597992ffbac completed May 23, 2026, 1:53 a.m.
Created at: April 22, 2026, 8:54 a.m.