Triple
T4280213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ORC |
E97127
|
entity |
| Predicate | abbreviationFor |
P43
|
FINISHED |
| Object | Optimized Row Columnar |
E426163
|
NE FINISHED |
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: Optimized Row Columnar | Statement: [ORC, abbreviationFor, Optimized Row Columnar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Optimized Row Columnar Context triple: [ORC, abbreviationFor, 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.
ColumnStore
ColumnStore is a columnar storage engine for MariaDB designed to support scalable, high-performance analytics and data warehousing workloads.
-
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.
xVelocity in-memory analytics engine
xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
-
E.
SparseArrays
SparseArrays is a Julia standard library module that provides data structures and operations for efficiently working with sparse matrices and related linear algebra.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35037b654819087abbb5ea231eefd |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7237b608190ab5aca56027344c4 |
completed | March 14, 2026, 8:37 p.m. |
Created at: March 12, 2026, 11:07 p.m.