Triple
T261185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisco Systems |
E5543
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | AppDynamics |
E33851
|
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: AppDynamics | Statement: [Cisco Systems, hasBrand, AppDynamics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AppDynamics Context triple: [Cisco Systems, hasBrand, AppDynamics]
-
A.
AppDynamics
chosen
AppDynamics is an application performance monitoring and observability company that provides tools to track, analyze, and optimize the performance of software applications and IT infrastructure.
-
B.
Omniture
Omniture was a leading web analytics and online marketing optimization company best known for its SiteCatalyst platform before being acquired by Adobe.
-
C.
BEA Systems
BEA Systems was a software company best known for its enterprise middleware and application server products that played a major role in early Java-based web and enterprise computing.
-
D.
Platform 6
Platform 6 is one of the passenger train platforms at Cambridge railway station in Cambridge, England.
-
E.
Tymshare
Tymshare was an influential American time-sharing and computer services company active in the 1960s–1980s that helped pioneer remote computing and software services for businesses.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d7428dc8190ae12b12a21fcc6cb |
completed | Feb. 28, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a386170dac81909a5ebf631f6037ab |
completed | March 1, 2026, 12:19 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.