Triple

T32211556
Position Surface form Disambiguated ID Type / Status
Subject Virtex FPGA family E822821 entity
Predicate hasVariant P455 FINISHED
Object Virtex-7
Virtex-7 is a high-performance Xilinx FPGA series built on advanced process technology, offering large logic capacity and high-speed transceivers for demanding digital design applications.
 E822821 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: Virtex-7 | Statement: [Virtex FPGA family, hasVariant, Virtex-7]
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: Virtex-7
Triple: [Virtex FPGA family, hasVariant, Virtex-7]
Generated description
Virtex-7 is a high-performance Xilinx FPGA series built on advanced process technology, offering large logic capacity and high-speed transceivers for demanding digital design 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_69f3490a3bec819097bc58d4731b9d08 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb93477481909115c4f41aedc7c0 completed May 3, 2026, 3:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349e99fdd481909cfcde7fe4c9b13a completed June 19, 2026, 1:42 a.m.
NEDg Description generation batch_6a349f3636f08190a0bfda93e0d62a24 completed June 19, 2026, 1:45 a.m.
NED2 Entity disambiguation (via description) batch_6a34a0b3ef448190b6e68eda0410de80 completed June 19, 2026, 1:51 a.m.
Created at: May 1, 2026, 12:37 a.m.