Triple

T27559740
Position Surface form Disambiguated ID Type / Status
Subject Direct3D 9 E695740 entity
Predicate supports P516 FINISHED
Object Shader Model 3.0
Shader Model 3.0 is a graphics programming feature set that introduced more advanced and flexible vertex and pixel shader capabilities, enabling richer visual effects and improved performance in modern 3D applications.
E1779562 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: Shader Model 3.0 | Statement: [Direct3D 9, supports, Shader Model 3.0]
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: Shader Model 3.0
Triple: [Direct3D 9, supports, Shader Model 3.0]
Generated description
Shader Model 3.0 is a graphics programming feature set that introduced more advanced and flexible vertex and pixel shader capabilities, enabling richer visual effects and improved performance in modern 3D applications.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fb839fc81909bdfc34aac33dcf6 completed May 2, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0cf04108190a88e56bf8b2c0af2 completed May 24, 2026, 10:19 a.m.
NEDg Description generation batch_6a12d169e8888190bf3c8e7f0718a3a5 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d270e0dc81909c04761a32c1e652 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 1:38 p.m.