Triple

T14388329
Position Surface form Disambiguated ID Type / Status
Subject Tensor Processing Unit E356779 entity
Predicate hasGeneration P455 FINISHED
Object TPU v5e
TPU v5e is a fifth-generation Google Tensor Processing Unit designed to provide efficient, scalable acceleration for machine learning workloads in the cloud.
 E97074 NE FINISHED

How this triple was built (4 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: TPU v5e | Statement: [Tensor Processing Unit, hasGeneration, TPU v5e]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TPU v5e
Context triple: [Tensor Processing Unit, hasGeneration, TPU v5e]
  • A. TPU
    A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
  • B. v5
    v5 is a major version of the React Router library that introduced a more declarative, component-based approach to routing in React applications.
  • C. TPE
    TPE is the three-letter IOC and international sporting code used to represent Chinese Taipei (Taiwan) in global competitions and events.
  • D. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • E. TU5
    TU5 is the IATA aircraft type designator for the Soviet-designed Tupolev Tu-154 medium-range narrow-body airliner.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: TPU v5e
Triple: [Tensor Processing Unit, hasGeneration, TPU v5e]
Generated description
TPU v5e is a fifth-generation Google Tensor Processing Unit designed to provide efficient, scalable acceleration for machine learning workloads in the cloud.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TPU v5e
Target entity description: TPU v5e is a fifth-generation Google Tensor Processing Unit designed to provide efficient, scalable acceleration for machine learning workloads in the cloud.
  • A. TPU chosen
    A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
  • B. v5
    v5 is a major version of the React Router library that introduced a more declarative, component-based approach to routing in React applications.
  • C. TPE
    TPE is the three-letter IOC and international sporting code used to represent Chinese Taipei (Taiwan) in global competitions and events.
  • D. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • E. TU5
    TU5 is the IATA aircraft type designator for the Soviet-designed Tupolev Tu-154 medium-range narrow-body airliner.
  • F. None of above.

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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90283b9c8190b50d30ad58bfe085 completed April 14, 2026, 7:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd551623608190ba1de09b423cc5e1 completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd5671340081909d87978be2a5522b completed May 8, 2026, 3:20 a.m.
NED2 Entity disambiguation (via description) batch_69fd57a6711881909429bba35ee867c6 completed May 8, 2026, 3:25 a.m.
Created at: April 10, 2026, 1:16 a.m.