Triple

T24291388
Position Surface form Disambiguated ID Type / Status
Subject Nicholls E605829 entity
Predicate hasNotableBearer P458 FINISHED
Object John G. Nicholls
John G. Nicholls is a neuroscientist best known for his influential work on the nervous system and for co-authoring the widely used textbook "From Neuron to Brain."
E2085886 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: John G. Nicholls | Statement: [Nicholls, hasNotableBearer, John G. Nicholls]
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: John G. Nicholls
Triple: [Nicholls, hasNotableBearer, John G. Nicholls]
Generated description
John G. Nicholls is a neuroscientist best known for his influential work on the nervous system and for co-authoring the widely used textbook "From Neuron to Brain."

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_69e29549335881909cbf27adcaba1cf0 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f29156ab8081909435b7178e9889bc completed April 29, 2026, 11:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a36cc5a09cc8190a117b64efe93fded completed June 20, 2026, 5:22 p.m.
NEDg Description generation batch_6a36cd6d7cd8819096aed8d710eafbba completed June 20, 2026, 5:27 p.m.
NED2 Entity disambiguation (via description) batch_6a36cecd322481908bfd584833273e39 completed June 20, 2026, 5:33 p.m.
Created at: April 18, 2026, 12:09 a.m.