Triple

T33038728
Position Surface form Disambiguated ID Type / Status
Subject George Villiers, 4th Earl of Clarendon E845393 entity
Predicate sibling P363 FINISHED
Object Thomas Hyde Villiers
Thomas Hyde Villiers was a 19th-century British politician and civil servant associated with the Whig party and known for his work on colonial and economic reform.
E2034041 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: Thomas Hyde Villiers | Statement: [George Villiers, 4th Earl of Clarendon, sibling, Thomas Hyde Villiers]
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: Thomas Hyde Villiers
Triple: [George Villiers, 4th Earl of Clarendon, sibling, Thomas Hyde Villiers]
Generated description
Thomas Hyde Villiers was a 19th-century British politician and civil servant associated with the Whig party and known for his work on colonial and economic reform.

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_69f34951348c8190b56746b0a7018182 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d30f752c81909caf901a140a3941 completed May 3, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e511fa448190875627d9cc37c6c9 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e654e7288190ae18f37300d8bfb6 completed June 19, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34e70605548190895680498d4f6066 completed June 19, 2026, 6:51 a.m.
Created at: May 1, 2026, 1:24 a.m.