Triple

T35969637
Position Surface form Disambiguated ID Type / Status
Subject AMD Instinct MI300 series E1040243 entity
Predicate includesModel P1393 FINISHED
Object AMD Instinct MI350X
AMD Instinct MI350X is a next-generation AMD data center GPU accelerator designed for high-performance computing and AI workloads, succeeding earlier MI300-series accelerators with improved performance and efficiency.
E2169265 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: AMD Instinct MI350X | Statement: [AMD Instinct MI300 series, includesModel, AMD Instinct MI350X]
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: AMD Instinct MI350X
Triple: [AMD Instinct MI300 series, includesModel, AMD Instinct MI350X]
Generated description
AMD Instinct MI350X is a next-generation AMD data center GPU accelerator designed for high-performance computing and AI workloads, succeeding earlier MI300-series accelerators with improved performance and efficiency.

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_69f76e27758c81909b711cf38a130aaf completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac23d1388190bdf9628b294943bd completed May 3, 2026, 8:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddf0ed74819097d9b5b75c347895 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38de652e14819096a312b01caea5fe completed June 22, 2026, 7:04 a.m.
NED2 Entity disambiguation (via description) batch_6a38dec27c5c8190822a585f2af6ef26 completed June 22, 2026, 7:05 a.m.
Created at: May 3, 2026, 4:07 p.m.