Triple
T1647849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadoop |
E35621
|
entity |
| Predicate | processingLayer |
P3274
|
FINISHED |
| Object | MapReduce |
E185673
|
NE FINISHED |
How this triple was built (3 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: MapReduce | Statement: [Hadoop, processingLayer, MapReduce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MapReduce Context triple: [Hadoop, processingLayer, MapReduce]
-
A.
MapReduce
chosen
MapReduce is a programming model and processing framework for distributed computation of large data sets across clusters of computers.
-
B.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
C.
Google MapReduce
Google MapReduce is a programming model and processing framework developed by Google for large-scale distributed data processing across clusters of commodity hardware.
-
D.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
E.
Google File System
Google File System is a distributed file system developed by Google to reliably store and process massive amounts of data across clusters of commodity hardware.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processingLayer Context triple: [Hadoop, processingLayer, MapReduce]
-
A.
operationalLayer
chosen
Indicates that one entity functions as an operational layer or level through which another entity’s activities, processes, or services are executed or managed.
-
B.
protocolLayer
Indicates a relationship where a communication protocol operates at, or is associated with, a specific layer in a protocol stack or network architecture.
-
C.
processFeature
Indicates that an entity performs or undergoes an operation that handles, transforms, or otherwise acts upon a specific feature.
-
D.
partOfProcess
Indicates that one event, step, or action occurs as a component or stage within a larger overall process.
-
E.
secondaryProcess
Indicates that an action or process occurs as a secondary, supporting, or subordinate operation relative to a primary process.
- F. None of above.
Provenance (4 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad681db3408190a3b469e319486419 |
completed | March 8, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.