Triple

T25960779
Position Surface form Disambiguated ID Type / Status
Subject Simon Kochen E645529 entity
Predicate academicAdvisor P167 FINISHED
Object Richard Brauer
Richard Brauer was a German-American mathematician renowned for his foundational contributions to algebra and representation theory, particularly Brauer groups and modular representation theory.
E1723639 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: Richard Brauer | Statement: [Simon Kochen, academicAdvisor, Richard Brauer]
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: Richard Brauer
Triple: [Simon Kochen, academicAdvisor, Richard Brauer]
Generated description
Richard Brauer was a German-American mathematician renowned for his foundational contributions to algebra and representation theory, particularly Brauer groups and modular representation theory.

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_69e77e85efc08190997da7fcf98bd300 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f604c60fe0819092ad09d1c5b0c100 completed May 2, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ae939d388190b1c703e36c0761e7 completed May 23, 2026, 1:41 p.m.
NEDg Description generation batch_6a11af6832f08190ab2673c8502f0526 completed May 23, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a11b0097edc81909327051db358c7b1 completed May 23, 2026, 1:47 p.m.
Created at: April 22, 2026, 8:47 a.m.