Triple

T19435496
Position Surface form Disambiguated ID Type / Status
Subject Oracle Database In-Memory E486215 entity
Predicate supportsFeature P203 FINISHED
Object In-Memory Dynamic Scans — NE NERFINISHED

How this triple was built (3 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: In-Memory Dynamic Scans | Statement: [Oracle Database In-Memory, supportsFeature, In-Memory Dynamic Scans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: In-Memory Dynamic Scans
Context triple: [Oracle Database In-Memory, supportsFeature, In-Memory Dynamic Scans]
  • A. xVelocity in-memory analytics engine
    xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
  • B. Live Partition Mobility
    Live Partition Mobility is an IBM Power Systems virtualization feature that enables running logical partitions (LPARs) to be moved between physical servers without downtime.
  • C. Automatic Storage Management
    Automatic Storage Management is Oracle's integrated volume manager and file system that simplifies and optimizes the management of database storage.
  • D. Log-Structured Merge-Tree
    A Log-Structured Merge-Tree (LSM-tree) is a write-optimized data structure that organizes data in sequential logs and periodically merges them to provide efficient writes and good read performance for key-value storage systems.
  • E. Security Administrator Tool for Analyzing Networks
    Security Administrator Tool for Analyzing Networks (SATAN) is an early network vulnerability scanner designed to help administrators identify and analyze security weaknesses in their systems.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: In-Memory Dynamic Scans
Target entity description: In-Memory Dynamic Scans are an Oracle Database In-Memory capability that automatically chooses between in-memory and on-disk access paths at runtime to optimize query performance based on current workload and data usage.
  • A. xVelocity in-memory analytics engine
    xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
  • B. Live Partition Mobility
    Live Partition Mobility is an IBM Power Systems virtualization feature that enables running logical partitions (LPARs) to be moved between physical servers without downtime.
  • C. Automatic Storage Management
    Automatic Storage Management is Oracle's integrated volume manager and file system that simplifies and optimizes the management of database storage.
  • D. Log-Structured Merge-Tree
    A Log-Structured Merge-Tree (LSM-tree) is a write-optimized data structure that organizes data in sequential logs and periodically merges them to provide efficient writes and good read performance for key-value storage systems.
  • E. Security Administrator Tool for Analyzing Networks
    Security Administrator Tool for Analyzing Networks (SATAN) is an early network vulnerability scanner designed to help administrators identify and analyze security weaknesses in their systems.
  • F. None of above. chosen

Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6336001488190a05f372779711ed2 completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:37 p.m.