Triple

T29741749
Position Surface form Disambiguated ID Type / Status
Subject Earl of Onslow E752626 entity
Predicate hasTitleHolder P1911 FINISHED
Object Arthur George Onslow, 3rd Earl of Onslow
Arthur George Onslow, 3rd Earl of Onslow, was a British peer and politician who served as a member of the House of Lords in the 19th century.
E1885439 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: Arthur George Onslow, 3rd Earl of Onslow | Statement: [Earl of Onslow, hasTitleHolder, Arthur George Onslow, 3rd Earl of Onslow]
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: Arthur George Onslow, 3rd Earl of Onslow
Triple: [Earl of Onslow, hasTitleHolder, Arthur George Onslow, 3rd Earl of Onslow]
Generated description
Arthur George Onslow, 3rd Earl of Onslow, was a British peer and politician who served as a member of the House of Lords in the 19th century.

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_69f0d62b064081908c1ae61cd68fb139 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f673633d288190b52ceb9f8a057c44 completed May 2, 2026, 9:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26e5e24eb08190934ef78347a317c8 completed June 8, 2026, 3:55 p.m.
NEDg Description generation batch_6a26e68b913481908d53ac147ad34f74 completed June 8, 2026, 3:58 p.m.
NED2 Entity disambiguation (via description) batch_6a26e7057a0c819089535980d5b98484 completed June 8, 2026, 4 p.m.
Created at: April 28, 2026, 7:48 p.m.