Triple

T18800670
Position Surface form Disambiguated ID Type / Status
Subject Amazon EMR E459746 entity
Predicate abbreviationOf P590 FINISHED
Object Amazon Elastic MapReduce NE NERFINISHED

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: Amazon Elastic MapReduce | Statement: [Amazon EMR, abbreviationOf, Amazon Elastic MapReduce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazon Elastic MapReduce
Context triple: [Amazon EMR, abbreviationOf, Amazon Elastic MapReduce]
  • A. Amazon EMR chosen
    Amazon EMR is a managed big data platform on AWS that simplifies running large-scale data processing frameworks like Apache Hadoop and Spark on elastic cloud clusters.
  • B. Amazon Redshift
    Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
  • C. Azure HDInsight
    Azure HDInsight is a fully managed cloud service from Microsoft that provides scalable Apache Hadoop, Spark, Hive, and other big data frameworks for processing and analyzing large datasets.
  • D. Amazon Kinesis
    Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
  • E. Amazon EC2
    Amazon EC2 is a scalable cloud computing service that provides virtual servers (instances) for running applications on Amazon Web Services infrastructure.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a02332d88190b68feea7f2f86d06 completed April 20, 2026, 3:40 a.m.
Created at: April 10, 2026, 11:53 a.m.