Triple

T1718408
Position Surface form Disambiguated ID Type / Status
Subject AppArmor E37339 entity
Predicate developer P73 FINISHED
Object Immunix
Immunix was a security-focused software company known for developing Linux security technologies, including the precursor to the AppArmor mandatory access control system.
 E193773 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: Immunix | Statement: [AppArmor, developer, Immunix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Immunix
Context triple: [AppArmor, developer, Immunix]
  • A. Setonix
    Setonix is a genus of small marsupials best known for including the quokka, a short-tailed wallaby native to southwestern Australia.
  • B. Zyvex
    Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
  • C. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • D. Ornex
    Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • E. Phenax
    Phenax is a small genus of flowering plants in the hemp family Cannabaceae, native to the Americas and typically found in tropical to subtropical regions.
  • 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: Immunix
Triple: [AppArmor, developer, Immunix]
Generated description
Immunix was a security-focused software company known for developing Linux security technologies, including the precursor to the AppArmor mandatory access control system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Immunix
Target entity description: Immunix was a security-focused software company known for developing Linux security technologies, including the precursor to the AppArmor mandatory access control system.
  • A. Setonix
    Setonix is a genus of small marsupials best known for including the quokka, a short-tailed wallaby native to southwestern Australia.
  • B. Zyvex
    Zyvex is a pioneering nanotechnology company known for its early work in molecular nanotechnology and advanced manufacturing.
  • C. Fremulon
    Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
  • D. Ornex
    Ornex is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • E. Phenax
    Phenax is a small genus of flowering plants in the hemp family Cannabaceae, native to the Americas and typically found in tropical to subtropical regions.
  • 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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa6337d8408190bdba8b50652d50ae completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ae6940c81909c1ebdfb0cdef5fc completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957bd63c819099a508ca5c4102cc completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97b18f9c8190a9c5ed80b5ed0195 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.