Triple

T26254237
Position Surface form Disambiguated ID Type / Status
Subject Griess algebra E656676 entity
Predicate alsoKnownAs P39 FINISHED
Object Monster algebra
Monster algebra is a large, highly structured commutative nonassociative algebra whose automorphism group is the Monster simple group, playing a central role in the theory of vertex operator algebras and monstrous moonshine.
E1713572 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: Monster algebra | Statement: [Griess algebra, alsoKnownAs, Monster algebra]
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: Monster algebra
Triple: [Griess algebra, alsoKnownAs, Monster algebra]
Generated description
Monster algebra is a large, highly structured commutative nonassociative algebra whose automorphism group is the Monster simple group, playing a central role in the theory of vertex operator algebras and monstrous moonshine.

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_69ee5b4d25ac819086acb51184602576 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60dcc29cc81908880bd825cb12141 completed May 2, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1185aaa938819094c6a7f051289d3d completed May 23, 2026, 10:47 a.m.
NEDg Description generation batch_6a11862050608190bf26431a0fb90b07 completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186c04c2c8190a5e70c9d9a5cbeb8 completed May 23, 2026, 10:51 a.m.
Created at: April 26, 2026, 9:08 p.m.