Triple

T1907629
Position Surface form Disambiguated ID Type / Status
Subject Linux Mint E38037 entity
Predicate includes P1393 FINISHED
Object mintReport
mintReport is a Linux Mint utility that helps users identify and troubleshoot system issues by providing diagnostic reports and recommendations.
 E212342 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: mintReport | Statement: [Linux Mint, includes, mintReport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: mintReport
Context triple: [Linux Mint, includes, mintReport]
  • A. MNT
    MNT is the Mongolian tögrög, the official national currency of Mongolia.
  • B. MTD
    MTD is the public bus transit agency serving the Champaign–Urbana metropolitan area in Illinois.
  • C. Muster
    Muster, commonly known as Aggie Muster, is a cherished Texas A&M University tradition in which Aggies worldwide gather annually to honor and remember fellow Aggies who have passed away.
  • D. MIP
    MIP is a U.S. Department of Defense funding and oversight framework that supports military intelligence activities, systems, and operations.
  • E. MUR
    MUR is the Italian Ministry responsible for national policies on universities, higher education, and scientific and technological research.
  • 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: mintReport
Triple: [Linux Mint, includes, mintReport]
Generated description
mintReport is a Linux Mint utility that helps users identify and troubleshoot system issues by providing diagnostic reports and recommendations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: mintReport
Target entity description: mintReport is a Linux Mint utility that helps users identify and troubleshoot system issues by providing diagnostic reports and recommendations.
  • A. MNT
    MNT is the Mongolian tögrög, the official national currency of Mongolia.
  • B. MTD
    MTD is the public bus transit agency serving the Champaign–Urbana metropolitan area in Illinois.
  • C. Muster
    Muster, commonly known as Aggie Muster, is a cherished Texas A&M University tradition in which Aggies worldwide gather annually to honor and remember fellow Aggies who have passed away.
  • D. MIP
    MIP is a U.S. Department of Defense funding and oversight framework that supports military intelligence activities, systems, and operations.
  • E. MUR
    MUR is the Italian Ministry responsible for national policies on universities, higher education, and scientific and technological research.
  • 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_69a8862a26088190aae5243695aeefc0 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1b44174819084fa06faf1930221 completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeafb063481908a08f5570acc5b57 completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adec22c5e48190af85fa4a1d4c5d8d completed March 8, 2026, 9:37 p.m.
NED2 Entity disambiguation (via description) batch_69adec9a840c8190a03f4de0f03a0e10 completed March 8, 2026, 9:39 p.m.
Created at: March 4, 2026, 7:35 p.m.