Triple
T17500127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Optimized Row Columnar |
E426163
|
entity |
| Predicate | comparedWith |
P278
|
FINISHED |
| Object | Apache Parquet |
—
|
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: Apache Parquet | Statement: [Optimized Row Columnar, comparedWith, Apache Parquet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Parquet Context triple: [Optimized Row Columnar, comparedWith, Apache Parquet]
-
A.
Apache Parquet
chosen
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.
parquet
The parquet is the French public prosecutor’s office, responsible for representing the state in criminal proceedings and directing public prosecutions.
-
C.
Apache ORC project
The Apache ORC project is an open-source initiative that develops the Optimized Row Columnar (ORC) file format for efficient, high-performance storage and processing of large-scale data in big data ecosystems.
-
D.
Apache Tez
Apache Tez is a distributed data processing framework designed for building high-performance batch and interactive data workflows on Hadoop.
-
E.
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.
- 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_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.