Triple

T7985628
Position Surface form Disambiguated ID Type / Status
Subject Apache Hive E185675 entity
Predicate supportsPlatform P203 FINISHED
Object Hadoop Distributed File System E187921 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: Hadoop Distributed File System | Statement: [Apache Hive, supportsPlatform, Hadoop Distributed File System]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hadoop Distributed File System
Context triple: [Apache Hive, supportsPlatform, Hadoop Distributed File System]
  • A. Hadoop
    Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
  • B. HDFS chosen
    HDFS (Hadoop Distributed File System) is a fault-tolerant, distributed file system designed to store and manage large volumes of data across clusters of commodity hardware.
  • C. Google File System
    Google File System is a distributed file system developed by Google to reliably store and process massive amounts of data across clusters of commodity hardware.
  • D. MapReduce
    MapReduce is a programming model and processing framework for distributed computation of large data sets across clusters of computers.
  • E. Apache HBase
    Apache HBase is a distributed, scalable, NoSQL database designed for real-time read/write access to large datasets, typically running on top of the Hadoop ecosystem.
  • 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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c4a55b881909a96133e56c0dffa completed March 31, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe17811081909c19f18c853617af completed April 1, 2026, 6:41 a.m.
Created at: March 30, 2026, 5:15 p.m.