Triple

T1971006
Position Surface form Disambiguated ID Type / Status
Subject Windows NT E42797 entity
Predicate fileSystem P1596 FINISHED
Object ReFS E192052 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: ReFS | Statement: [Windows NT, fileSystem, ReFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ReFS
Context triple: [Windows NT, fileSystem, ReFS]
  • A. ReFS chosen
    ReFS (Resilient File System) is a Microsoft file system designed to improve data integrity, availability, and scalability over the older NTFS format.
  • B. NTFS
    NTFS (New Technology File System) is a Microsoft-developed file system known for its support of large volumes, file permissions, encryption, and advanced reliability features used in modern Windows operating systems.
  • C. ReiserFS
    ReiserFS is a journaling file system for Linux known for its efficient handling of small files and advanced tree-based storage structures.
  • D. XFS
    XFS is a high-performance 64-bit journaling file system originally developed by SGI, widely used on Linux for handling large files and parallel I/O workloads.
  • E. F2FS
    F2FS (Flash-Friendly File System) is a Linux file system optimized for NAND flash-based storage devices, designed to improve performance and lifespan on solid-state media.
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3d2836c8190a35cb6d8e2dd4bdf completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfbd9a2dc81909f86fdfa9c646dd0 completed March 8, 2026, 10:44 p.m.
Created at: March 4, 2026, 7:36 p.m.