Triple

T477754
Position Surface form Disambiguated ID Type / Status
Subject GNU Emacs E9097 entity
Predicate notableComponent P7734 FINISHED
Object Gnus
Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
 E59588 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: Gnus | Statement: [GNU Emacs, notableComponent, Gnus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gnus
Context triple: [GNU Emacs, notableComponent, Gnus]
  • A. Bolt Beranek and Newman
    Bolt Beranek and Newman was a pioneering American research and engineering firm best known for its foundational role in developing the ARPANET, a precursor to the modern internet.
  • B. Grok
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • C. Jerome
    Jerome was an early Christian scholar and theologian best known for translating the Bible into Latin (the Vulgate) and for his influential biblical commentaries.
  • D. Ficker
    Ficker is the birth surname of renowned American ballerina Suzanne Farrell, one of the most celebrated muses of choreographer George Balanchine.
  • E. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • 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: Gnus
Triple: [GNU Emacs, notableComponent, Gnus]
Generated description
Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gnus
Target entity description: Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
  • A. Bolt Beranek and Newman
    Bolt Beranek and Newman was a pioneering American research and engineering firm best known for its foundational role in developing the ARPANET, a precursor to the modern internet.
  • B. Grok
    Grok is an AI chatbot developed by xAI, designed to provide conversational access to real-time information and reasoning capabilities.
  • C. Jerome
    Jerome was an early Christian scholar and theologian best known for translating the Bible into Latin (the Vulgate) and for his influential biblical commentaries.
  • D. Ficker
    Ficker is the birth surname of renowned American ballerina Suzanne Farrell, one of the most celebrated muses of choreographer George Balanchine.
  • E. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f03f3fbc81909af6e4496d5e6c2a completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a46804b90881908422851eeb9bbba1 completed March 1, 2026, 4:23 p.m.
NEDg Description generation batch_69a46901d5c08190af7ea8b01206505c completed March 1, 2026, 4:27 p.m.
NED2 Entity disambiguation (via description) batch_69a4696c35c08190890e8159983e2efb completed March 1, 2026, 4:29 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.