Triple
T1622454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver Lake Partners |
E35061
|
entity |
| Predicate | notableInvestment |
P3488
|
FINISHED |
| Object | Avaya |
E90705
|
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: Avaya | Statement: [Silver Lake Partners, notableInvestment, Avaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avaya Context triple: [Silver Lake Partners, notableInvestment, Avaya]
-
A.
Avaya
chosen
Avaya is an American multinational technology company specializing in business communications, unified communications, and contact center solutions for enterprises and organizations worldwide.
-
B.
Polycom
Polycom is a telecommunications company best known for its audio and video conferencing solutions and collaboration technologies used in businesses worldwide.
-
C.
Tandberg
Tandberg is a Norwegian company best known for its video conferencing and telepresence solutions, which became part of Cisco Systems after its acquisition.
-
D.
Opsware
Opsware was a data center automation and IT infrastructure management software company, best known for being co-founded by Marc Andreessen and later acquired by Hewlett-Packard.
-
E.
Genesys
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.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a909cf3c7481909ddbe6a6596bb0c8 |
completed | March 5, 2026, 4:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58c9ed4c8190a546ec4977f60695 |
completed | March 8, 2026, 11:08 a.m. |
Created at: March 4, 2026, 7:28 p.m.