Triple
T17500199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apache ORC |
E426165
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Apache Optimized Row Columnar |
—
|
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 Optimized Row Columnar | Statement: [Apache ORC, fullName, Apache Optimized Row Columnar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Optimized Row Columnar Context triple: [Apache ORC, fullName, Apache Optimized Row Columnar]
-
A.
Optimized Row Columnar
chosen
Optimized Row Columnar (ORC) is a highly efficient, columnar storage file format commonly used in big data systems like Apache Hive to enable fast query performance and effective data compression.
-
B.
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.
-
C.
ColumnStore
ColumnStore is a columnar storage engine for MariaDB designed to support scalable, high-performance analytics and data warehousing workloads.
-
D.
RCFile
RCFile is a columnar storage file format designed for efficient data processing and querying in Hadoop-based systems.
-
E.
H-Store
H-Store is a pioneering in-memory, distributed OLTP database system designed for high-throughput transaction processing on modern multicore hardware.
- 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.