Triple

T17676575
Position Surface form Disambiguated ID Type / Status
Subject Mersenne Twister E440656 entity
Predicate designedBy P184 FINISHED
Object Takuji Nishimura
Takuji Nishimura is a Japanese mathematician and computer scientist best known as a co-creator of the widely used Mersenne Twister pseudorandom number generator.
E2099699 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: Takuji Nishimura | Statement: [Mersenne Twister, designedBy, Takuji Nishimura]
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: Takuji Nishimura
Triple: [Mersenne Twister, designedBy, Takuji Nishimura]
Generated description
Takuji Nishimura is a Japanese mathematician and computer scientist best known as a co-creator of the widely used Mersenne Twister pseudorandom number generator.

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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6d9ab88190ab0e25eac8b0101c completed April 19, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3729b8e0b08190a930e4d355b143f8 completed June 21, 2026, midnight
NEDg Description generation batch_6a372beefb9081908c8fe969e86599c4 completed June 21, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a372cb51db48190825e0b9114b84c4a completed June 21, 2026, 12:13 a.m.
Created at: April 10, 2026, 10:01 a.m.