Triple

T35086626
Position Surface form Disambiguated ID Type / Status
Subject Craggs E1012593 entity
Predicate hasNotableBearer P458 FINISHED
Object Fred Craggs
Fred Craggs is a notable individual distinguished enough to be specifically cited as a prominent bearer of the surname Craggs.
E2129594 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: Fred Craggs | Statement: [Craggs, hasNotableBearer, Fred Craggs]
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: Fred Craggs
Triple: [Craggs, hasNotableBearer, Fred Craggs]
Generated description
Fred Craggs is a notable individual distinguished enough to be specifically cited as a prominent bearer of the surname Craggs.

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_69f76dd32c008190853aef6028f60208 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78bacbe5c8190a0a871529e80052e completed May 3, 2026, 5:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37fb0460d08190b83dc559c08098d1 completed June 21, 2026, 2:53 p.m.
NEDg Description generation batch_6a37fc128968819088382c45052692ee completed June 21, 2026, 2:58 p.m.
NED2 Entity disambiguation (via description) batch_6a37fcd7cb108190bb34b69ce43aafed completed June 21, 2026, 3:01 p.m.
Created at: May 3, 2026, 4:01 p.m.