Triple

T32211558
Position Surface form Disambiguated ID Type / Status
Subject Virtex FPGA family E822821 entity
Predicate hasVariant P455 FINISHED
Object Virtex UltraScale+
Virtex UltraScale+ is a high-performance Xilinx FPGA series designed for advanced applications requiring massive parallel processing, high-speed connectivity, and low power consumption.
 E1826981 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 UltraScale+ | Statement: [Virtex FPGA family, hasVariant, Virtex UltraScale+]
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 UltraScale+
Triple: [Virtex FPGA family, hasVariant, Virtex UltraScale+]
Generated description
Virtex UltraScale+ is a high-performance Xilinx FPGA series designed for advanced applications requiring massive parallel processing, high-speed connectivity, and low power consumption.

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_6a34b1457b808190baf15c383d53b443 completed June 19, 2026, 3:02 a.m.
NEDg Description generation batch_6a34b226f710819086b2d0bee27a8c79 completed June 19, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_6a34b2b0f36c8190ab30af3d30024b97 completed June 19, 2026, 3:08 a.m.
Created at: May 1, 2026, 12:37 a.m.