Triple

T17498846
Position Surface form Disambiguated ID Type / Status
Subject Amazon Athena E426142 entity
Predicate supportsDataFormat P8463 FINISHED
Object Apache Hudi 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: Apache Hudi | Statement: [Amazon Athena, supportsDataFormat, Apache Hudi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apache Hudi
Context triple: [Amazon Athena, supportsDataFormat, Apache Hudi]
  • A. Apache Parquet
    Apache Parquet is a columnar storage file format optimized for efficient data compression and query performance in big data processing frameworks such as Apache Hadoop and Apache Spark.
  • B. Apache Gobblin
    Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
  • 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. Delta Lake storage layer
    Delta Lake storage layer is an open-source data storage framework that brings ACID transactions, schema enforcement, and reliability to data lakes, particularly in big data and analytics environments.
  • E. Apache Flink
    Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
  • 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: Apache Hudi
Target entity description: Apache Hudi is an open-source data lake framework that enables efficient data ingestion, storage, and incremental processing on large-scale datasets, particularly in cloud object stores.
  • A. Apache Parquet
    Apache Parquet is a columnar storage file format optimized for efficient data compression and query performance in big data processing frameworks such as Apache Hadoop and Apache Spark.
  • B. Apache Gobblin
    Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
  • 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. Delta Lake storage layer chosen
    Delta Lake storage layer is an open-source data storage framework that brings ACID transactions, schema enforcement, and reliability to data lakes, particularly in big data and analytics environments.
  • E. Apache Flink
    Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
  • F. None of above.

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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4521028048190aa7c4023a72a12f4 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.