Triple

T17500128
Position Surface form Disambiguated ID Type / Status
Subject Optimized Row Columnar E426163 entity
Predicate comparedWith P278 FINISHED
Object Apache Avro 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 Avro | Statement: [Optimized Row Columnar, comparedWith, Apache Avro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apache Avro
Context triple: [Optimized Row Columnar, comparedWith, Apache Avro]
  • 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 Tez
    Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
  • D. Apache Pig
    Apache Pig is a high-level platform for creating MapReduce programs used to analyze large data sets in the Hadoop ecosystem.
  • E. Apache Kafka
    Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
  • 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 Avro
Target entity description: Apache Avro is a data serialization system and file format in the Apache Hadoop ecosystem that provides compact, fast, binary data encoding with rich schema support and dynamic typing.
  • 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 Tez
    Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
  • D. Apache Pig
    Apache Pig is a high-level platform for creating MapReduce programs used to analyze large data sets in the Hadoop ecosystem.
  • E. Apache Kafka
    Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
  • F. None of above. chosen

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_69e452112ff0819089c2951baba90102 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.