Triple

T18134232
Position Surface form Disambiguated ID Type / Status
Subject Google Cloud TPU v3 E434094 entity
Predicate supports P516 FINISHED
Object TPU Pods
TPU Pods are large-scale clusters of interconnected Tensor Processing Units designed to accelerate massive machine learning workloads with high-performance distributed training.
E1308864 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 Pods | Statement: [Google Cloud TPU v3, supports, TPU Pods]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TPU Pods
Context triple: [Google Cloud TPU v3, supports, TPU Pods]
  • A. P-POD
    P-POD is a standardized deployment system designed to safely house and launch CubeSat miniature satellites into space from a host vehicle.
  • B. SkyPod
    SkyPod is the highest observation deck of Toronto’s CN Tower, offering panoramic views from near the top of the landmark skyscraper.
  • C. Pave Claw pod
    The Pave Claw pod is an external gun pod system designed to house and deploy the GAU-12/U 25mm rotary cannon on compatible aircraft.
  • D. Station F
    Station F is a massive startup campus and innovation hub in Paris that hosts hundreds of early-stage companies, investors, and support programs under one roof.
  • E. Pallets
    Pallets is an open-source organization best known for creating and maintaining popular Python web development tools such as Flask, Jinja, and Werkzeug.
  • 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 Pods
Triple: [Google Cloud TPU v3, supports, TPU Pods]
Generated description
TPU Pods are large-scale clusters of interconnected Tensor Processing Units designed to accelerate massive machine learning workloads with high-performance distributed training.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: TPU Pods
Target entity description: TPU Pods are large-scale clusters of interconnected Tensor Processing Units designed to accelerate massive machine learning workloads with high-performance distributed training.
  • A. P-POD
    P-POD is a standardized deployment system designed to safely house and launch CubeSat miniature satellites into space from a host vehicle.
  • B. SkyPod
    SkyPod is the highest observation deck of Toronto’s CN Tower, offering panoramic views from near the top of the landmark skyscraper.
  • C. Pave Claw pod
    The Pave Claw pod is an external gun pod system designed to house and deploy the GAU-12/U 25mm rotary cannon on compatible aircraft.
  • D. Station F
    Station F is a massive startup campus and innovation hub in Paris that hosts hundreds of early-stage companies, investors, and support programs under one roof.
  • E. Pallets
    Pallets is an open-source organization best known for creating and maintaining popular Python web development tools such as Flask, Jinja, and Werkzeug.
  • 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de055c608190a090c2737904e5f9 completed April 19, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0385489c3c8190b7e20d6c8c75ea16 completed May 12, 2026, 7:53 p.m.
NEDg Description generation batch_6a038acaf8f48190b88562c0a1df9109 completed May 12, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a038b4132bc8190992cae1400894fef completed May 12, 2026, 8:19 p.m.
Created at: April 10, 2026, 10:29 a.m.