Triple

T8918322
Position Surface form Disambiguated ID Type / Status
Subject Reiser4 E212348 entity
Predicate developer P73 FINISHED
Object Namesys E212346 NE FINISHED

How this triple was built (2 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: [Reiser4, developer, Namesys]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namesys
Context triple: [Reiser4, developer, Namesys]
  • A. Namesys chosen
    Namesys was a software company best known for developing the ReiserFS journaling file system for Linux.
  • B. Plaxo
    Plaxo was an online address book and social networking service that helped users manage and synchronize their contact information across multiple platforms.
  • C. 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.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca8393b1808190bd4336787ffa2c40 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66120eb08190913ab6c42f26ffb8 completed April 1, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc932f9848190a2571cfc28353088 completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:56 p.m.