Triple

T34545654
Position Surface form Disambiguated ID Type / Status
Subject Cantor normal form E886917 entity
Predicate relatedConcept P37 FINISHED
Object Cantor–Bendixson rank
The Cantor–Bendixson rank is an ordinal-valued measure that classifies points in a topological space according to the stage at which they are removed by iteratively deleting isolated points in the Cantor–Bendixson derivative process.
 E2099810 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: Cantor–Bendixson rank | Statement: [Cantor normal form, relatedConcept, Cantor–Bendixson rank]
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: Cantor–Bendixson rank
Triple: [Cantor normal form, relatedConcept, Cantor–Bendixson rank]
Generated description
The Cantor–Bendixson rank is an ordinal-valued measure that classifies points in a topological space according to the stage at which they are removed by iteratively deleting isolated points in the Cantor–Bendixson derivative process.

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_69f349cff89081908f91e0b064f4833e completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7201fc32c8190a79a85a7a4f63662 completed May 3, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3729f5443c8190a1e372c3ad6eafbd completed June 21, 2026, 12:01 a.m.
NEDg Description generation batch_6a372bc1f7e88190a6c32aba4a653c00 completed June 21, 2026, 12:09 a.m.
NED2 Entity disambiguation (via description) batch_6a372c34f9f08190856a6b1cb7860443 completed June 21, 2026, 12:11 a.m.
Created at: May 1, 2026, 2:02 a.m.