Triple
T7388246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goya inference processor |
E170435
|
entity |
| Predicate | hasSoftwareStack |
P21680
|
FINISHED |
| Object | Habana software stack |
—
|
LITERAL 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: Habana software stack | Statement: [Goya inference processor, hasSoftwareStack, Habana software stack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSoftwareStack Context triple: [Goya inference processor, hasSoftwareStack, Habana software stack]
-
A.
hasSoftwareCompatibilityWith
Indicates that one software system can operate correctly and effectively with another software system, without conflicts or required modifications.
-
B.
hasSoftwareStandard
Indicates that an entity conforms to, implements, or is governed by a specified software-related standard.
-
C.
technologyStack
chosen
Indicates the set of technologies, tools, and platforms used together to build or run a system, application, or project.
-
D.
usesSoftware
Indicates that one entity employs or operates a particular software application or system to perform tasks or functions.
-
E.
supportsSoftwareEcosystem
Indicates that one entity provides resources, compatibility, or infrastructure that enables another entity’s software ecosystem to function, grow, or be maintained.
- F. None of above.
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_69c68a5e2c9081909e713ce866e0060a |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1f3f5f48190aabe69ba79cbcb93 |
completed | March 27, 2026, 9:09 p.m. |
| PD | Predicate disambiguation | batch_69c6f0309cc88190b55d278969400294 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:09 p.m.