Triple

T7985572
Position Surface form Disambiguated ID Type / Status
Subject Apache Storm E185674 entity
Predicate supportsIntegrationWith P5090 FINISHED
Object Apache Cassandra E358077 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: Apache Cassandra | Statement: [Apache Storm, supportsIntegrationWith, Apache Cassandra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apache Cassandra
Context triple: [Apache Storm, supportsIntegrationWith, Apache Cassandra]
  • A. Apache Cassandra chosen
    Apache Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers with high availability and no single point of failure.
  • B. 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.
  • C. Apache Hive
    Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
  • D. Apache Storm
    Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
  • E. Amazon Neptune
    Amazon Neptune is a fully managed graph database service designed for storing and querying highly connected data using popular graph models and query languages.
  • 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_69cc567cfe548190bbd163a32c340bcc completed March 31, 2026, 11:19 p.m.
Created at: March 30, 2026, 5:15 p.m.