Triple
T17499020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Splunk |
E426145
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Splunk On-Call |
—
|
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 On-Call | Statement: [Splunk, product, Splunk On-Call]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Splunk On-Call Context triple: [Splunk, product, Splunk On-Call]
-
A.
Opsgenie
chosen
Opsgenie is a cloud-based incident management and alerting platform that helps DevOps and IT teams respond quickly to critical outages and service disruptions.
-
B.
PagerDuty
PagerDuty is a cloud-based incident management and alerting platform that helps IT and DevOps teams detect, triage, and resolve operational issues in real time.
-
C.
Splunk
Splunk is a data analytics platform that specializes in collecting, indexing, and analyzing machine-generated data for monitoring, security, and operational intelligence.
-
D.
Alertmanager
Alertmanager is a Prometheus ecosystem component that handles alert processing, deduplication, grouping, and routing to notification channels.
-
E.
VividCortex
VividCortex is a database performance monitoring and analytics platform designed to help teams optimize and troubleshoot production database workloads in real time.
- 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.