Triple
T7939927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flux |
E184363
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object | Alertmanager |
E699841
|
NE FINISHED |
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: Alertmanager | Statement: [Flux, integratesWith, Alertmanager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alertmanager Context triple: [Flux, integratesWith, Alertmanager]
-
A.
Alertmanager
chosen
Alertmanager is a Prometheus ecosystem component that handles alert processing, deduplication, grouping, and routing to notification channels.
-
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.
VividCortex
VividCortex is a database performance monitoring and analytics platform designed to help teams optimize and troubleshoot production database workloads in real time.
-
D.
Growl (third‑party notification system for many users)
Growl is a once-popular third-party notification system for macOS that provided customizable, system-wide alerts for many different applications.
-
E.
Grafana
Grafana is an open-source analytics and visualization platform used to create interactive dashboards and monitor metrics from various data sources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b0983388190a77e8d5d899c5130 |
completed | March 31, 2026, 3:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe019a094819082baecdcb007c84f |
completed | March 31, 2026, 2:54 p.m. |
Created at: March 30, 2026, 5:08 p.m.