Triple

T34860429
Position Surface form Disambiguated ID Type / Status
Subject John E1004852 entity
Predicate givenNameUsedBy P16531 FINISHED
Object William John Cunningham
William John Cunningham is an individual known by the given name John, about whom further widely recognized public information is not readily available.
E2134134 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: William John Cunningham | Statement: [John, givenNameUsedBy, William John Cunningham]
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: William John Cunningham
Triple: [John, givenNameUsedBy, William John Cunningham]
Generated description
William John Cunningham is an individual known by the given name John, about whom further widely recognized public information is not readily available.

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_69f76dbb678081909a247b9b5e1a73ac completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78164dc208190af8f42a3b7c21513 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819c2a5e48190ab9e8b77853ee657 completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381a61041c8190ab5b92cd2b7332d0 completed June 21, 2026, 5:07 p.m.
NED2 Entity disambiguation (via description) batch_6a381aebf1dc8190b4218f36891f5e1c completed June 21, 2026, 5:10 p.m.
Created at: May 3, 2026, 4 p.m.