Triple

T34909451
Position Surface form Disambiguated ID Type / Status
Subject Burney family E1006822 entity
Predicate hasMember P10 FINISHED
Object Edward Francis Burney
Edward Francis Burney was an English painter and illustrator of the late 18th and early 19th centuries, known for his satirical and literary-themed works.
 E2125740 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 Francis Burney | Statement: [Burney family, hasMember, Edward Francis Burney]
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 Francis Burney
Triple: [Burney family, hasMember, Edward Francis Burney]
Generated description
Edward Francis Burney was an English painter and illustrator of the late 18th and early 19th centuries, known for his satirical and literary-themed works.

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_69f76dc1b4a081909b4c6e4d8ec0aa2d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f781ee4b188190b020eb2ff685c6ad completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37cfd3b90081909a770e42d931950d completed June 21, 2026, 11:49 a.m.
NEDg Description generation batch_6a37d07ba708819081b552b8a69313e5 completed June 21, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37d1935d9881909cee3755fec2d996 completed June 21, 2026, 11:57 a.m.
Created at: May 3, 2026, 4 p.m.