Triple

T33761012
Position Surface form Disambiguated ID Type / Status
Subject sieve of Eratosthenes E865104 entity
Predicate relatedAlgorithm P25130 FINISHED
Object sieve of Atkin
The sieve of Atkin is an advanced, highly optimized algorithm for finding all prime numbers up to a given limit, designed to be more efficient than the classical sieve of Eratosthenes for large ranges.
E2065182 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: sieve of Atkin | Statement: [sieve of Eratosthenes, relatedAlgorithm, sieve of Atkin]
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: sieve of Atkin
Triple: [sieve of Eratosthenes, relatedAlgorithm, sieve of Atkin]
Generated description
The sieve of Atkin is an advanced, highly optimized algorithm for finding all prime numbers up to a given limit, designed to be more efficient than the classical sieve of Eratosthenes for large ranges.

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_69f3498d3b748190aa3c4006c1f32f38 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fc6130a88190aa23b826fc7c5266 completed May 3, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c995f188190b40b5eff42eff403 completed June 20, 2026, 9:25 a.m.
NEDg Description generation batch_6a365d1385648190a48b5817d3ec67f9 completed June 20, 2026, 9:27 a.m.
NED2 Entity disambiguation (via description) batch_6a365e57afc48190bd3fad174217b2c3 completed June 20, 2026, 9:33 a.m.
Created at: May 1, 2026, 1:45 a.m.