Triple
T15989629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloudera |
E387790
|
entity |
| Predicate | usesTechnology |
P1485
|
FINISHED |
| Object |
Apache Impala
Apache Impala is a massively parallel, SQL-on-Hadoop query engine designed for low-latency, interactive analysis of large-scale data stored in distributed systems.
|
E1190439
|
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: Apache Impala | Statement: [Cloudera, usesTechnology, Apache Impala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apache Impala Context triple: [Cloudera, usesTechnology, Apache Impala]
-
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.
IMPALA
IMPALA is a scalable deep reinforcement learning architecture designed for efficient distributed training of agents across many tasks and environments.
-
C.
Hive
The Hive is the Zerg’s ultimate tech structure in StarCraft, enabling advanced units, upgrades, and late-game capabilities.
-
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
- 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: Apache Impala Triple: [Cloudera, usesTechnology, Apache Impala]
Generated description
Apache Impala is a massively parallel, SQL-on-Hadoop query engine designed for low-latency, interactive analysis of large-scale data stored in distributed systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Apache Impala Target entity description: Apache Impala is a massively parallel, SQL-on-Hadoop query engine designed for low-latency, interactive analysis of large-scale data stored in distributed systems.
-
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.
IMPALA
IMPALA is a scalable deep reinforcement learning architecture designed for efficient distributed training of agents across many tasks and environments.
-
C.
Hive
The Hive is the Zerg’s ultimate tech structure in StarCraft, enabling advanced units, upgrades, and late-game capabilities.
-
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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157829ec08190aa4a683e29a0148a |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf1cb1388190b1ebccc6705e5974 |
completed | May 10, 2026, 12:19 a.m. |
| NEDg | Description generation | batch_69ffcf9d6c5c8190b10abdf70aed7ddf |
completed | May 10, 2026, 12:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffd96de9288190ab1727e7864dcaa6 |
completed | May 10, 2026, 1:03 a.m. |
Created at: April 10, 2026, 4:54 a.m.