Triple
T12562463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Stonebraker |
E295382
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object |
Aurora (stream processing system)
Aurora is a pioneering data stream management system designed for high-performance, real-time processing of continuous data streams, developed under the leadership of database researcher Michael Stonebraker.
|
E991164
|
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: Aurora (stream processing system) | Statement: [Michael Stonebraker, knownFor, Aurora (stream processing system)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aurora (stream processing system) Context triple: [Michael Stonebraker, knownFor, Aurora (stream processing system)]
-
A.
Apache Samza
Apache Samza is a distributed stream processing framework designed for scalable, fault-tolerant processing of real-time data streams, often used with Apache Kafka and YARN.
-
B.
Apache Storm
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
-
C.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
D.
IBM Streams
IBM Streams is a high-performance stream processing platform that enables real-time ingestion, analysis, and correlation of large-scale data in motion for enterprise applications.
-
E.
Apache Gobblin
Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
- 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: Aurora (stream processing system) Triple: [Michael Stonebraker, knownFor, Aurora (stream processing system)]
Generated description
Aurora is a pioneering data stream management system designed for high-performance, real-time processing of continuous data streams, developed under the leadership of database researcher Michael Stonebraker.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aurora (stream processing system) Target entity description: Aurora is a pioneering data stream management system designed for high-performance, real-time processing of continuous data streams, developed under the leadership of database researcher Michael Stonebraker.
-
A.
Apache Samza
Apache Samza is a distributed stream processing framework designed for scalable, fault-tolerant processing of real-time data streams, often used with Apache Kafka and YARN.
-
B.
Apache Storm
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
-
C.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
D.
IBM Streams
IBM Streams is a high-performance stream processing platform that enables real-time ingestion, analysis, and correlation of large-scale data in motion for enterprise applications.
-
E.
Apache Gobblin
Apache Gobblin is an open-source distributed data integration framework designed for large-scale data ingestion, replication, and lifecycle management across diverse data sources and sinks.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95494ae1c81908b9ee14b8ef92a65 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558da7e0819086860bfaf394e2d8 |
completed | May 2, 2026, 7:50 p.m. |
| NEDg | Description generation | batch_69f65a0f1b2881908a7cb21c9de1a5c2 |
completed | May 2, 2026, 8:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f65ad4424c8190933759cca5d73c22 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 8, 2026, 11:48 p.m.