Triple

T30026714
Position Surface form Disambiguated ID Type / Status
Subject NVIDIA Pascal architecture E762898 entity
Predicate usedInProductLine P4614 FINISHED
Object NVIDIA Titan X (Pascal)
NVIDIA Titan X (Pascal) is a high-end NVIDIA graphics card based on the Pascal architecture, designed primarily for enthusiast gaming, VR, and GPU-accelerated compute workloads.
E1916769 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: NVIDIA Titan X (Pascal) | Statement: [NVIDIA Pascal architecture, usedInProductLine, NVIDIA Titan X (Pascal)]
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: NVIDIA Titan X (Pascal)
Triple: [NVIDIA Pascal architecture, usedInProductLine, NVIDIA Titan X (Pascal)]
Generated description
NVIDIA Titan X (Pascal) is a high-end NVIDIA graphics card based on the Pascal architecture, designed primarily for enthusiast gaming, VR, and GPU-accelerated compute workloads.

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_69f2246ee6e48190b69e837b913b398a completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f679ac62ac8190b1ab93bf5803e0a9 completed May 2, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27abfedd708190a5974776a136c5c4 completed June 9, 2026, 6 a.m.
NEDg Description generation batch_6a27ad542b548190bf8286915784bf01 completed June 9, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a27ade3972c8190b3bb7951caca8cc4 completed June 9, 2026, 6:08 a.m.
Created at: April 29, 2026, 6:48 p.m.