Triple

T8611439
Position Surface form Disambiguated ID Type / Status
Subject eMMC E203921 entity
Predicate comparedTo P278 FINISHED
Object UFS
UFS (Universal Flash Storage) is a high-speed flash memory standard commonly used in smartphones and other mobile devices, offering faster data transfer and improved efficiency compared to older storage technologies.
 E745346 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: UFS | Statement: [eMMC, comparedTo, UFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UFS
Context triple: [eMMC, comparedTo, UFS]
  • A. UFS
    UFS (Unix File System) is a long-standing, robust file system widely used in Unix-like operating systems, particularly BSD variants, for organizing and managing data on disk.
  • B. 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.
  • C. UHS
    UHS is the stock ticker symbol for Universal Health Services, a major U.S.-based hospital and healthcare services company.
  • D. U3
    U3 is one of the main lines of the Nuremberg U-Bahn rapid transit system in Nuremberg, Germany.
  • E. U3
    U3 is a line of the Berlin U-Bahn rapid transit system serving several districts in the German capital.
  • 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: UFS
Triple: [eMMC, comparedTo, UFS]
Generated description
UFS (Universal Flash Storage) is a high-speed flash memory standard commonly used in smartphones and other mobile devices, offering faster data transfer and improved efficiency compared to older storage technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UFS
Target entity description: UFS (Universal Flash Storage) is a high-speed flash memory standard commonly used in smartphones and other mobile devices, offering faster data transfer and improved efficiency compared to older storage technologies.
  • A. UFS
    UFS (Unix File System) is a long-standing, robust file system widely used in Unix-like operating systems, particularly BSD variants, for organizing and managing data on disk.
  • B. 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.
  • C. UHS
    UHS is the stock ticker symbol for Universal Health Services, a major U.S.-based hospital and healthcare services company.
  • D. U3
    U3 is one of the main lines of the Nuremberg U-Bahn rapid transit system in Nuremberg, Germany.
  • E. U3
    U3 is a line of the Berlin U-Bahn rapid transit system serving several districts in the German capital.
  • 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_69ca832c23e4819095a9f3eea4a21828 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46fc31e08190aab5ab8f92f3315c completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea91456a88190a7416b0f1a0327d6 completed April 2, 2026, 5:36 p.m.
NEDg Description generation batch_69cea9e685388190a4be9d2135dc02d0 completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaababe2c8190bc47430d33bfdbaa completed April 2, 2026, 5:43 p.m.
Created at: March 30, 2026, 6:25 p.m.