Triple

T20627069
Position Surface form Disambiguated ID Type / Status
Subject Helly’s theorem E506847 entity
Predicate namedAfter P63 FINISHED
Object Eduard Helly
Eduard Helly was an Austrian mathematician best known for his foundational contributions to functional analysis and convex geometry, including the classical Helly’s theorem.
E2117151 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: Eduard Helly | Statement: [Helly’s theorem, namedAfter, Eduard Helly]
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: Eduard Helly
Triple: [Helly’s theorem, namedAfter, Eduard Helly]
Generated description
Eduard Helly was an Austrian mathematician best known for his foundational contributions to functional analysis and convex geometry, including the classical Helly’s theorem.

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_69e0b4bd4a0081908d4e97a590a33fb2 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe576c081909231dc0d7304b9a9 completed April 20, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786b1cf408190a05ec092820cb539 completed June 21, 2026, 6:37 a.m.
NEDg Description generation batch_6a378f7c14f881908b059b59ec6c892b completed June 21, 2026, 7:15 a.m.
NED2 Entity disambiguation (via description) batch_6a37900b238c8190bda9ac2ff1af848e completed June 21, 2026, 7:17 a.m.
Created at: April 16, 2026, 11:42 a.m.