Triple

T816538
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow E17662 entity
Predicate supportsHardware P5090 FINISHED
Object 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.
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 | Statement: [TensorFlow, supportsHardware, TPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TPU
Context triple: [TensorFlow, supportsHardware, TPU]
  • A. TPE
    TPE is the three-letter IOC and international sporting code used to represent Chinese Taipei (Taiwan) in global competitions and events.
  • B. TPA
    TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
  • C. PLA
    The PLA is the unified military organization of the People's Republic of China, encompassing its ground, naval, air, rocket, and strategic support forces.
  • D. T-MEC
    T-MEC is the Spanish-language name for the United States–Mexico–Canada Agreement, the trade pact that replaced NAFTA in North America.
  • E. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • 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
Triple: [TensorFlow, supportsHardware, TPU]
Generated description
A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TPU
Target entity description: A TPU (Tensor Processing Unit) is a specialized hardware accelerator designed by Google to efficiently perform large-scale machine learning and deep learning computations.
  • A. TPE
    TPE is the three-letter IOC and international sporting code used to represent Chinese Taipei (Taiwan) in global competitions and events.
  • B. TPA
    TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
  • C. PLA
    The PLA is the unified military organization of the People's Republic of China, encompassing its ground, naval, air, rocket, and strategic support forces.
  • D. T-MEC
    T-MEC is the Spanish-language name for the United States–Mexico–Canada Agreement, the trade pact that replaced NAFTA in North America.
  • E. TEC
    TEC is the commonly used acronym for the Episcopal Church, a mainline Anglican Christian denomination based in the United States.
  • F. None of above. chosen

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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab621d2c819083f10bff4f66c482 completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8d1a448190be8494fa2776615a completed March 3, 2026, 11:23 p.m.
NEDg Description generation batch_69a78bd0a1d48190907434a17853dfb1 completed March 4, 2026, 1:33 a.m.
NED2 Entity disambiguation (via description) batch_69a78c3a57d88190a994ed44bcb2d8d1 completed March 4, 2026, 1:34 a.m.
Created at: March 1, 2026, 7:38 p.m.