Triple

T21885707
Position Surface form Disambiguated ID Type / Status
Subject William Rowley E540397 entity
Predicate coAuthor P398 FINISHED
Object George Wilkins
George Wilkins was an early 17th-century English playwright and pamphleteer associated with the Jacobean theatre scene and collaborations with contemporaries such as William Shakespeare.
E1812677 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: George Wilkins | Statement: [William Rowley, coAuthor, George Wilkins]
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: George Wilkins
Triple: [William Rowley, coAuthor, George Wilkins]
Generated description
George Wilkins was an early 17th-century English playwright and pamphleteer associated with the Jacobean theatre scene and collaborations with contemporaries such as William Shakespeare.

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_69e0c479a98081908ce333853fdd4348 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f118ec147481908903e2f24e049d8f completed April 28, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606e1bc188190829c97ea704d4927 completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a161feb3d908190b4b36e31cc2f5755 completed May 26, 2026, 10:34 p.m.
NED2 Entity disambiguation (via description) batch_6a16207483b0819082e9327aa1bf63f2 completed May 26, 2026, 10:36 p.m.
Created at: April 16, 2026, 7:05 p.m.