Triple
T15410850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia N8 |
E368585
|
entity |
| Predicate | gpuModel |
P11228
|
FINISHED |
| Object | Broadcom BCM2727 |
E950058
|
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: Broadcom BCM2727 | Statement: [Nokia N8, gpuModel, Broadcom BCM2727]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Broadcom BCM2727 Context triple: [Nokia N8, gpuModel, Broadcom BCM2727]
-
A.
Broadcom BCM2763
chosen
The Broadcom BCM2763 is a mobile multimedia processor and graphics chip designed to accelerate high-definition video and advanced graphics in smartphones and portable devices.
-
B.
Raspberry Pi
Raspberry Pi is a low-cost, credit card–sized single-board computer widely used for education, DIY electronics projects, and lightweight computing tasks.
-
C.
BeagleBone Black
BeagleBone Black is a low-cost, community-supported single-board computer based on an ARM Cortex-A8 processor, commonly used for embedded systems, robotics, and hardware prototyping.
-
D.
BeagleBoard
BeagleBoard is a low-power, open-hardware single-board computer designed for embedded systems, prototyping, and educational use.
-
E.
Nvidia Tegra K1
The Nvidia Tegra K1 is a mobile system-on-chip that introduced desktop-class Kepler GPU architecture to smartphones and tablets, significantly boosting their graphics and compute performance.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea600b48190a3dbca1a68a2a1cd |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7356548190af5651ab0bc03ab9 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:20 a.m.