Triple
T7985655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apache Hive |
E185675
|
entity |
| Predicate | usesComponent |
P35
|
FINISHED |
| Object |
Hive Metastore
Hive Metastore is a central metadata repository service that stores and manages schema and table information for data warehousing systems like Apache Hive.
|
E705292
|
NE FINISHED |
How this triple was built (4 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: Hive Metastore | Statement: [Apache Hive, usesComponent, Hive Metastore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hive Metastore Context triple: [Apache Hive, usesComponent, Hive Metastore]
-
A.
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.
-
B.
Apache HBase
Apache HBase is a distributed, scalable, NoSQL database designed for real-time read/write access to large datasets, typically running on top of the Hadoop ecosystem.
-
C.
HDFS
HDFS (Hadoop Distributed File System) is a fault-tolerant, distributed file system designed to store and manage large volumes of data across clusters of commodity hardware.
-
D.
Greenplum
Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
-
E.
Apache Oozie
Apache Oozie is a workflow scheduler system designed to manage and coordinate Hadoop jobs such as MapReduce, Pig, and Hive in complex data processing pipelines.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hive Metastore Triple: [Apache Hive, usesComponent, Hive Metastore]
Generated description
Hive Metastore is a central metadata repository service that stores and manages schema and table information for data warehousing systems like Apache Hive.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hive Metastore Target entity description: Hive Metastore is a central metadata repository service that stores and manages schema and table information for data warehousing systems like Apache Hive.
-
A.
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.
-
B.
Apache HBase
Apache HBase is a distributed, scalable, NoSQL database designed for real-time read/write access to large datasets, typically running on top of the Hadoop ecosystem.
-
C.
HDFS
HDFS (Hadoop Distributed File System) is a fault-tolerant, distributed file system designed to store and manage large volumes of data across clusters of commodity hardware.
-
D.
Greenplum
Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
-
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 (5 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c4a55b881909a96133e56c0dffa |
completed | March 31, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0e6f3c48190a0132fa90eec6420 |
completed | March 31, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_69cc46c221848190848c7e017e532a16 |
completed | March 31, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc480d2f40819085046a1d0c9d05e0 |
completed | March 31, 2026, 10:17 p.m. |
Created at: March 30, 2026, 5:15 p.m.