Triple
T7428241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAA |
E171420
|
entity |
| Predicate | represents |
P129
|
FINISHED |
| Object | Tandberg |
E33850
|
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: Tandberg | Statement: [TAA, represents, Tandberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tandberg Context triple: [TAA, represents, Tandberg]
-
A.
Tandberg
chosen
Tandberg is a Norwegian company best known for its video conferencing and telepresence solutions, which became part of Cisco Systems after its acquisition.
-
B.
Polycom
Polycom is a telecommunications company best known for its audio and video conferencing solutions and collaboration technologies used in businesses worldwide.
-
C.
Avaya
Avaya is an American multinational technology company specializing in business communications, unified communications, and contact center solutions for enterprises and organizations worldwide.
-
D.
Tesira
Tesira is Biamp Systems’ networked audio and video platform known for scalable, DSP-based solutions in professional AV installations.
-
E.
Biamp Systems
Biamp Systems is an American professional audio and video equipment manufacturer known for its conferencing, signal processing, and networked media solutions used in commercial and institutional installations worldwide.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f306bfe481909f99f6792de95ffc |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81f0e28e88190805108dff740dda3 |
completed | March 28, 2026, 6:33 p.m. |
Created at: March 27, 2026, 3:12 p.m.