Triple
T29736977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ROG Strix |
E752488
|
entity |
| Predicate | softwareEcosystem |
P10387
|
FINISHED |
| Object |
Armoury Crate
Armoury Crate is ASUS’s centralized software platform for managing system settings, RGB lighting, and gaming features across compatible ROG hardware.
|
E1882353
|
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: Armoury Crate | Statement: [ROG Strix, softwareEcosystem, Armoury Crate]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Armoury Crate Triple: [ROG Strix, softwareEcosystem, Armoury Crate]
Generated description
Armoury Crate is ASUS’s centralized software platform for managing system settings, RGB lighting, and gaming features across compatible ROG hardware.
Provenance (5 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67334fe2081908edc2dcea6e231a6 |
completed | May 2, 2026, 9:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26aa8a40908190aeef7ca1945b0148 |
completed | June 8, 2026, 11:42 a.m. |
| NEDg | Description generation | batch_6a26b5ab72f88190a4ee83b459d4fcbf |
completed | June 8, 2026, 12:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a26b99bc3cc8190b3c5af05105cd8e2 |
completed | June 8, 2026, 12:46 p.m. |
Created at: April 28, 2026, 7:45 p.m.