Triple

T34307947
Position Surface form Disambiguated ID Type / Status
Subject Prince George of Wales E880361 entity
Predicate godparent P19584 FINISHED
Object William van Cutsem
William van Cutsem is a close family friend of the British royal family and a member of a prominent English aristocratic family, known in part for his longstanding connection to Prince William.
E2095938 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: William van Cutsem | Statement: [Prince George of Wales, godparent, William van Cutsem]
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: William van Cutsem
Triple: [Prince George of Wales, godparent, William van Cutsem]
Generated description
William van Cutsem is a close family friend of the British royal family and a member of a prominent English aristocratic family, known in part for his longstanding connection to Prince William.

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_69f349b8bb6c8190ad12a7957a574f04 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7133c80ec81908522d8692fdd117c completed May 3, 2026, 9:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370dad234c81909ce8a0b05bb3a5e3 completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e7dcd88819091a402e550189e46 completed June 20, 2026, 10:04 p.m.
NED2 Entity disambiguation (via description) batch_6a370f2dba508190af182d53a385b955 completed June 20, 2026, 10:07 p.m.
Created at: May 1, 2026, 1:57 a.m.