Triple
T1647828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadoop |
E35621
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object |
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.
|
E187921
|
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: HDFS | Statement: [Hadoop, hasComponent, HDFS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HDFS Context triple: [Hadoop, hasComponent, HDFS]
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
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.
-
C.
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.
-
D.
YARN
YARN (Yet Another Resource Negotiator) is Hadoop’s cluster resource management and job scheduling framework that coordinates and allocates system resources for distributed data processing applications.
-
E.
MapReduce
MapReduce is a programming model and processing framework for distributed computation of large data sets across clusters of computers.
- 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: HDFS Triple: [Hadoop, hasComponent, HDFS]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HDFS Target entity description: 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.
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
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.
-
C.
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.
-
D.
YARN
YARN (Yet Another Resource Negotiator) is Hadoop’s cluster resource management and job scheduling framework that coordinates and allocates system resources for distributed data processing applications.
-
E.
MapReduce
MapReduce is a programming model and processing framework for distributed computation of large data sets across clusters of computers.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a640ea88190822906da575d5165 |
completed | March 5, 2026, 4:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad681db3408190a3b469e319486419 |
completed | March 8, 2026, 12:14 p.m. |
| NEDg | Description generation | batch_69ad692a4078819080c3a89166917081 |
completed | March 8, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad698929f88190af97fc915d29a5b5 |
completed | March 8, 2026, 12:20 p.m. |
Created at: March 4, 2026, 7:29 p.m.