Triple
T7985901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apache Flume |
E185680
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object |
Logger Sink
Logger Sink is a Flume sink that writes event data to application logs, typically for debugging or simple monitoring purposes.
|
E705301
|
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: Logger Sink | Statement: [Apache Flume, supports, Logger Sink]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logger Sink Context triple: [Apache Flume, supports, Logger Sink]
-
A.
Loggers
Loggers is the athletics nickname for the University of Puget Sound’s varsity sports teams, reflecting the region’s historical ties to the logging industry.
-
B.
LOG
LOG is the ICAO airline designator assigned to Loganair, a regional airline based in Scotland.
-
C.
Syslog
Syslog is a standard protocol used for message logging and event notification across network devices and computer systems.
-
D.
Logierait
Logierait is a small village in Perth and Kinross, Scotland, known as the birthplace of the philosopher and historian Adam Ferguson.
-
E.
Oracle Logging
Oracle Logging is a cloud-native log management and analytics service within Oracle Cloud Infrastructure that centralizes, stores, and helps monitor and analyze logs from various OCI resources and applications.
- 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: Logger Sink Triple: [Apache Flume, supports, Logger Sink]
Generated description
Logger Sink is a Flume sink that writes event data to application logs, typically for debugging or simple monitoring purposes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Logger Sink Target entity description: Logger Sink is a Flume sink that writes event data to application logs, typically for debugging or simple monitoring purposes.
-
A.
Loggers
Loggers is the athletics nickname for the University of Puget Sound’s varsity sports teams, reflecting the region’s historical ties to the logging industry.
-
B.
LOG
LOG is the ICAO airline designator assigned to Loganair, a regional airline based in Scotland.
-
C.
Syslog
Syslog is a standard protocol used for message logging and event notification across network devices and computer systems.
-
D.
Logierait
Logierait is a small village in Perth and Kinross, Scotland, known as the birthplace of the philosopher and historian Adam Ferguson.
-
E.
Oracle Logging
Oracle Logging is a cloud-native log management and analytics service within Oracle Cloud Infrastructure that centralizes, stores, and helps monitor and analyze logs from various OCI resources and applications.
- 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_69cb3c4b87e48190a797f5363c8f0a04 |
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.