Triple

T4600210
Position Surface form Disambiguated ID Type / Status
Subject Google Cloud Dataproc E100303 entity
Predicate supportsStorage P203 FINISHED
Object HDFS 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: HDFS | Statement: [Google Cloud Dataproc, supportsStorage, HDFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HDFS
Context triple: [Google Cloud Dataproc, supportsStorage, HDFS]
  • A. 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.
  • B. Hadoop
    Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets 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. 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.
  • E. GPFS (IBM Spectrum Scale)
    GPFS (IBM Spectrum Scale) is IBM’s high-performance, scalable clustered file system designed for large-scale data storage and parallel access in enterprise and HPC environments.
  • 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5971f448819090f6e76c7d3ffc2d completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa5a7aac8190b540b80816d55051 completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.