Triple
T3430167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Genesys |
E72316
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Genesys |
E72316
|
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: Genesys | Statement: [Genesys, hasAbbreviation, Genesys]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genesys Context triple: [Genesys, hasAbbreviation, Genesys]
-
A.
Genesys
chosen
Genesys is a global customer experience and contact center technology company known for its cloud-based solutions that help businesses manage and optimize customer interactions.
-
B.
Avaya
Avaya is an American multinational technology company specializing in business communications, unified communications, and contact center solutions for enterprises and organizations worldwide.
-
C.
Perot Systems
Perot Systems was an American information technology services and consulting company founded by Ross Perot that provided outsourcing, systems integration, and technology solutions to businesses and governments worldwide.
-
D.
Unisys
Unisys is an American global information technology company known for providing IT services, software, and infrastructure solutions to government and commercial clients.
-
E.
Siebel Systems
Siebel Systems was a leading enterprise software company best known for pioneering customer relationship management (CRM) solutions for large organizations.
- 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9bd61908190a7bdd01f24334fc3 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3547b1b3481909646bf36e8461ff4 |
completed | March 13, 2026, 12:04 a.m. |
Created at: March 8, 2026, 3:15 p.m.