Triple

T7937563
Position Surface form Disambiguated ID Type / Status
Subject DNF E184321 entity
Predicate abbreviationOf P590 FINISHED
Object Dandified YUM E184320 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: Dandified YUM | Statement: [DNF, abbreviationOf, Dandified YUM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dandified YUM
Context triple: [DNF, abbreviationOf, Dandified YUM]
  • A. YUM
    YUM is the stock ticker symbol for Yum! Brands, the multinational fast-food corporation that owns KFC, Taco Bell, and Pizza Hut.
  • B. YUM chosen
    YUM is a command-line package management utility for RPM-based Linux distributions that automatically handles software installation, updates, and dependency resolution.
  • C. libdnf
    libdnf is a software library that provides the core dependency resolution and package management functionality used by the DNF package manager on RPM-based Linux distributions.
  • D. Katello
    Katello is an open-source systems management and content lifecycle tool that provides software repository, subscription, and configuration management capabilities, commonly used as a core component of Red Hat Satellite.
  • E. Python packaging ecosystem
    The Python packaging ecosystem is the collection of tools, standards, and services that enable building, distributing, and installing Python software packages, including components like package formats, repositories, and upload utilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe019a094819082baecdcb007c84f completed March 31, 2026, 2:54 p.m.
Created at: March 30, 2026, 5:08 p.m.