Triple

T25354885
Position Surface form Disambiguated ID Type / Status
Subject Somerset family E635792 entity
Predicate hasNotableMember P304 FINISHED
Object Edward Somerset, 4th Earl of Worcester
Edward Somerset, 4th Earl of Worcester, was an influential English nobleman and courtier who served as a trusted advisor and high-ranking official under Queen Elizabeth I and King James I.
E1691427 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: Edward Somerset, 4th Earl of Worcester | Statement: [Somerset family, hasNotableMember, Edward Somerset, 4th Earl of Worcester]
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: Edward Somerset, 4th Earl of Worcester
Triple: [Somerset family, hasNotableMember, Edward Somerset, 4th Earl of Worcester]
Generated description
Edward Somerset, 4th Earl of Worcester, was an influential English nobleman and courtier who served as a trusted advisor and high-ranking official under Queen Elizabeth I and King James I.

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_69e75a9ac5d881909387ed766e20cd47 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f49e0075b88190ba626e6591f24ed8 completed May 1, 2026, 12:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c11c179481909bc3c1c58b17451d completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c1f3ae208190b3cdc518e83bbc7f completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2b0c540819086fe2b0fef3f76d1 completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 1:35 p.m.