Triple

T5964122
Position Surface form Disambiguated ID Type / Status
Subject Yum! Brands E132710 entity
Predicate tickerSymbol P1447 FINISHED
Object YUM
YUM is the stock ticker symbol for Yum! Brands, the multinational fast-food corporation that owns KFC, Taco Bell, and Pizza Hut.
 E559051 NE FINISHED

How this triple was built (4 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: YUM | Statement: [Yum! Brands, tickerSymbol, YUM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: YUM
Context triple: [Yum! Brands, tickerSymbol, YUM]
  • A. YUM
    YUM is a command-line package management utility for RPM-based Linux distributions that automatically handles software installation, updates, and dependency resolution.
  • B. RPM
    RPM is a widely used package management system originally developed for Linux distributions to build, install, and manage software packages.
  • C. 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.
  • D. Apt
    Apt is a historic market town in southeastern France’s Vaucluse department, known for its candied fruit production and Provençal charm.
  • E. YEM
    YEM is the three-letter ISO 3166-1 alpha-3 country code assigned to Yemen for international identification and data standards.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: YUM
Triple: [Yum! Brands, tickerSymbol, YUM]
Generated description
YUM is the stock ticker symbol for Yum! Brands, the multinational fast-food corporation that owns KFC, Taco Bell, and Pizza Hut.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: YUM
Target entity description: YUM is the stock ticker symbol for Yum! Brands, the multinational fast-food corporation that owns KFC, Taco Bell, and Pizza Hut.
  • A. YUM
    YUM is a command-line package management utility for RPM-based Linux distributions that automatically handles software installation, updates, and dependency resolution.
  • B. RPM
    RPM is a widely used package management system originally developed for Linux distributions to build, install, and manage software packages.
  • C. 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.
  • D. Apt
    Apt is a historic market town in southeastern France’s Vaucluse department, known for its candied fruit production and Provençal charm.
  • E. YEM
    YEM is the three-letter ISO 3166-1 alpha-3 country code assigned to Yemen for international identification and data standards.
  • F. None of above. chosen

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_69c0086c2364819091e9fe2f58fa2517 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a0240cc81909d7c75c7e6d630f7 completed March 22, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3f32e8481908a6075684287c412 completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0ebfa3a9c81908a183f995350366b completed March 23, 2026, 7:30 a.m.
NED2 Entity disambiguation (via description) batch_69c0ec61672c8190b98cead75cac84d5 completed March 23, 2026, 7:31 a.m.
Created at: March 22, 2026, 4:03 p.m.