Triple

T26378389
Position Surface form Disambiguated ID Type / Status
Subject IPU E660958 entity
Predicate usedWith P4791 FINISHED
Object Graphcore SDK
Graphcore SDK is a software development kit that provides tools, libraries, and APIs for building and optimizing machine learning and high-performance computing applications on Graphcore’s IPU hardware.
E170436 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: Graphcore SDK | Statement: [IPU, usedWith, Graphcore SDK]
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: Graphcore SDK
Triple: [IPU, usedWith, Graphcore SDK]
Generated description
Graphcore SDK is a software development kit that provides tools, libraries, and APIs for building and optimizing machine learning and high-performance computing applications on Graphcore’s IPU 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_69ee812a698881908d6a58265995fa39 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f61072d5f481908ef99900df8d23e7 completed May 2, 2026, 2:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aeb3003c81909fc47f6138842cf2 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11afcce63c8190ac822c630de91480 completed May 23, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_6a11b08396c8819094b627b21872f43b completed May 23, 2026, 1:49 p.m.
Created at: April 26, 2026, 11:03 p.m.