Triple
T17498847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Athena |
E426142
|
entity |
| Predicate | supportsDataFormat |
P8463
|
FINISHED |
| Object | Apache Iceberg |
—
|
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 Iceberg | Statement: [Amazon Athena, supportsDataFormat, Apache Iceberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Iceberg Context triple: [Amazon Athena, supportsDataFormat, Apache Iceberg]
-
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.
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.
-
C.
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.
-
D.
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.
-
E.
Apache Tez
Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
- 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 Iceberg Target entity description: Apache Iceberg is an open table format for huge analytic datasets that enables reliable, high-performance querying and data management in data lake environments.
-
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.
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.
-
C.
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.
-
D.
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.
-
E.
Apache Tez
Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
- 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_69e4521028048190aa7c4023a72a12f4 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.