Triple

T1489754
Position Surface form Disambiguated ID Type / Status
Subject Noether's problem E29549 entity
Predicate typicalSetup P28573 FINISHED
Object a finite group G acting on a rational function field k(x_g : g in G) LITERAL 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: a finite group G acting on a rational function field k(x_g : g in G) | Statement: [Noether's problem, typicalSetup, a finite group G acting on a rational function field k(x_g : g in G)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalSetup
Context triple: [Noether's problem, typicalSetup, a finite group G acting on a rational function field k(x_g : g in G)]
  • A. typicalDeployment
    Indicates that one entity represents the standard or most commonly used deployment configuration or pattern for the other entity.
  • B. typicalEngine
    Indicates that an entity is the standard or commonly used engine for another entity (such as a vehicle, device, or system).
  • C. typicalInstrumentation
    Indicates the usual or standard set of instruments commonly associated with performing or realizing something (such as a work, genre, or piece).
  • D. establishesTest
    Indicates that an entity creates or sets up a test or testing procedure for another entity.
  • E. setUp
    Indicates establishing, arranging, or preparing something so that it is ready for use or for a particular purpose.
  • F. None of above. chosen

Provenance (4 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_69a498da82e08190ba833330d05f380f completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c233ec819087e1233af02aabfc completed March 1, 2026, 11:07 p.m.
PD Predicate disambiguation batch_69a4c48902808190a8028d359bcf123e completed March 1, 2026, 10:58 p.m.
PDg Predicate description generation batch_69a4c52c703c8190a56389b09d97659f completed March 1, 2026, 11:01 p.m.
Created at: March 1, 2026, 8:12 p.m.