Triple
T4013744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avaya |
E90705
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Avaya OneCloud |
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 OneCloud | Statement: [Avaya, product, Avaya OneCloud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avaya OneCloud Context triple: [Avaya, product, Avaya OneCloud]
-
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.
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.
-
C.
Polycom
Polycom is a telecommunications company best known for its audio and video conferencing solutions and collaboration technologies used in businesses worldwide.
-
D.
Lifesize Communications
Lifesize Communications is a company specializing in high-definition video conferencing and collaboration solutions for businesses.
-
E.
Twilio
Twilio is a cloud communications platform company that enables developers and businesses to integrate voice, messaging, video, and authentication capabilities into their applications via APIs.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8ad6348190b71feaf8c18c90c2 |
completed | March 9, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c73e6048190a59a8d8bc12c907d |
completed | March 14, 2026, 11:54 a.m. |
Created at: March 9, 2026, 3:35 p.m.