Triple

T4654874
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow Extended E102383 entity
Predicate hasComponent P35 FINISHED
Object BulkInferrer
BulkInferrer is a TensorFlow Extended (TFX) component used to run large-scale batch inference with trained machine learning models on sizable datasets.
 E457350 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: BulkInferrer | Statement: [TensorFlow Extended, hasComponent, BulkInferrer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BulkInferrer
Context triple: [TensorFlow Extended, hasComponent, BulkInferrer]
  • A. Datu
    Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
  • B. Robust.AI
    Robust.AI is a robotics company focused on building practical, intelligent robot systems for real-world environments, co-founded by renowned roboticist Rodney Brooks.
  • C. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • D. Goya inference processor
    The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
  • E. BIME Analytics
    BIME Analytics is a cloud-based business intelligence and data visualization platform known for enabling companies to analyze and report on customer and operational data.
  • 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: BulkInferrer
Triple: [TensorFlow Extended, hasComponent, BulkInferrer]
Generated description
BulkInferrer is a TensorFlow Extended (TFX) component used to run large-scale batch inference with trained machine learning models on sizable datasets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BulkInferrer
Target entity description: BulkInferrer is a TensorFlow Extended (TFX) component used to run large-scale batch inference with trained machine learning models on sizable datasets.
  • A. Datu
    Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
  • B. Robust.AI
    Robust.AI is a robotics company focused on building practical, intelligent robot systems for real-world environments, co-founded by renowned roboticist Rodney Brooks.
  • C. Tabularium
    The Tabularium was the official records office of ancient Rome, a monumental state archive building overlooking the Roman Forum.
  • D. Goya inference processor
    The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
  • E. BIME Analytics
    BIME Analytics is a cloud-based business intelligence and data visualization platform known for enabling companies to analyze and report on customer and operational data.
  • 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6317ba70819089145766d3462e57 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaef125c819097d79f25608302dc completed March 21, 2026, 1:57 a.m.
NEDg Description generation batch_69bdfc0964c881909e6b98a1c8ea747f completed March 21, 2026, 2:01 a.m.
NED2 Entity disambiguation (via description) batch_69bdfce1be788190ae3418df301e5136 completed March 21, 2026, 2:05 a.m.
Created at: March 20, 2026, 1:14 p.m.