Triple

T1907651
Position Surface form Disambiguated ID Type / Status
Subject ReiserFS E38038 entity
Predicate developer P73 FINISHED
Object Namesys
Namesys was a software company best known for developing the ReiserFS journaling file system for Linux.
E212346 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: Namesys | Statement: [ReiserFS, developer, Namesys]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namesys
Context triple: [ReiserFS, developer, Namesys]
  • A. VeriSign
    VeriSign is an American technology company best known for operating key internet infrastructure, including managing the .com and .net top-level domains and providing critical DNS and security services.
  • B. GoDaddy
    GoDaddy is a major American internet domain registrar and web hosting company known for providing online presence and website services to individuals and businesses worldwide.
  • C. Nom.com
    Nom.com was a live video streaming and social platform focused on food and cooking, co-founded by YouTube co-founder Steve Chen.
  • D. Genesys
    Genesys is a global customer experience and contact center technology company known for its cloud-based solutions that help businesses manage and optimize customer interactions.
  • E. Norid
    Norid is the Norwegian registry responsible for administering the country’s .no top-level internet domain.
  • 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: Namesys
Triple: [ReiserFS, developer, Namesys]
Generated description
Namesys was a software company best known for developing the ReiserFS journaling file system for Linux.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Namesys
Target entity description: Namesys was a software company best known for developing the ReiserFS journaling file system for Linux.
  • A. VeriSign
    VeriSign is an American technology company best known for operating key internet infrastructure, including managing the .com and .net top-level domains and providing critical DNS and security services.
  • B. GoDaddy
    GoDaddy is a major American internet domain registrar and web hosting company known for providing online presence and website services to individuals and businesses worldwide.
  • C. Nom.com
    Nom.com was a live video streaming and social platform focused on food and cooking, co-founded by YouTube co-founder Steve Chen.
  • D. Genesys
    Genesys is a global customer experience and contact center technology company known for its cloud-based solutions that help businesses manage and optimize customer interactions.
  • E. Norid
    Norid is the Norwegian registry responsible for administering the country’s .no top-level internet domain.
  • 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.