Triple

T18705042
Position Surface form Disambiguated ID Type / Status
Subject Transform E457346 entity
Predicate partOf P40 FINISHED
Object TFX pipeline NE NERFINISHED

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: TFX pipeline | Statement: [Transform, partOf, TFX pipeline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TFX pipeline
Context triple: [Transform, partOf, TFX pipeline]
  • A. TensorFlow Transform
    TensorFlow Transform is a TensorFlow-based library for performing scalable, full-pass data preprocessing and feature engineering that can be applied consistently in both training and serving.
  • B. TensorFlow I/O
    TensorFlow I/O is an extension library for TensorFlow that provides specialized input/output operations and dataset integrations for a wide range of file formats and data sources beyond the core framework’s built-in support.
  • C. Kubeflow Pipelines
    Kubeflow Pipelines is a platform for building, deploying, and managing end-to-end machine learning workflows on Kubernetes using containerized components.
  • D. TFX chosen
    TFX is an end-to-end production machine learning platform built on TensorFlow that supports scalable data processing, model training, validation, and deployment.
  • E. TFX
    TFX is a French television channel owned and operated by the TF1 Group, offering a mix of entertainment, series, and reality programming.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5671665bc8190b9b4a4ce4ec5b2eb completed April 19, 2026, 11:36 p.m.
Created at: April 10, 2026, 11:49 a.m.