Triple
T17499180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Kinesis Data Firehose |
E426148
|
entity |
| Predicate | deliversTo |
P31954
|
FINISHED |
| Object | Splunk |
—
|
NE NERFINISHED |
How this triple was built (2 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: Splunk | Statement: [Amazon Kinesis Data Firehose, deliversTo, Splunk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Splunk Context triple: [Amazon Kinesis Data Firehose, deliversTo, Splunk]
-
A.
Splunk
chosen
Splunk is a data analytics platform that specializes in collecting, indexing, and analyzing machine-generated data for monitoring, security, and operational intelligence.
-
B.
Sumo Logic
Sumo Logic is a cloud-native machine data analytics and log management platform that helps organizations monitor, troubleshoot, and secure their applications and infrastructure in real time.
-
C.
ArcSight
ArcSight is a cybersecurity platform specializing in security information and event management (SIEM) to help organizations detect, analyze, and respond to threats.
-
D.
Datadog
Datadog is a cloud-based monitoring and security platform that provides observability into applications, infrastructure, logs, and metrics for modern DevOps and IT teams.
-
E.
New Relic
New Relic is a software analytics and application performance monitoring company that provides tools for tracking and optimizing the performance of web and mobile applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4521028048190aa7c4023a72a12f4 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.