Triple

T17521088
Position Surface form Disambiguated ID Type / Status
Subject TensorFlow Estimators E426678 entity
Predicate hasExampleImplementation P127768 FINISHED
Object DNNLinearCombinedRegressor
DNNLinearCombinedRegressor is a TensorFlow Estimator that combines deep neural network and linear (wide) models to perform regression tasks.
 E1274574 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: DNNLinearCombinedRegressor | Statement: [TensorFlow Estimators, hasExampleImplementation, DNNLinearCombinedRegressor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DNNLinearCombinedRegressor
Context triple: [TensorFlow Estimators, hasExampleImplementation, DNNLinearCombinedRegressor]
  • A. DNNLinearCombinedClassifier
    DNNLinearCombinedClassifier is a TensorFlow Estimator that combines deep neural network and linear (wide) models into a single classifier for tasks like structured data prediction.
  • B. LinearRegressor
    LinearRegressor is a TensorFlow Estimator that implements linear regression models for predicting continuous values from input features.
  • C. LinearClassifier
    LinearClassifier is a TensorFlow Estimator that implements a linear model for classification tasks, typically using features combined with linear weights to predict discrete labels.
  • D. LogisticRegression
    LogisticRegression is a scikit-learn machine learning estimator that models the probability of class membership using a linear decision boundary with logistic (sigmoid) or related link functions.
  • E. TensorFlow Estimators
    TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
  • 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: DNNLinearCombinedRegressor
Triple: [TensorFlow Estimators, hasExampleImplementation, DNNLinearCombinedRegressor]
Generated description
DNNLinearCombinedRegressor is a TensorFlow Estimator that combines deep neural network and linear (wide) models to perform regression tasks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DNNLinearCombinedRegressor
Target entity description: DNNLinearCombinedRegressor is a TensorFlow Estimator that combines deep neural network and linear (wide) models to perform regression tasks.
  • A. DNNLinearCombinedClassifier
    DNNLinearCombinedClassifier is a TensorFlow Estimator that combines deep neural network and linear (wide) models into a single classifier for tasks like structured data prediction.
  • B. LinearRegressor
    LinearRegressor is a TensorFlow Estimator that implements linear regression models for predicting continuous values from input features.
  • C. LinearClassifier
    LinearClassifier is a TensorFlow Estimator that implements a linear model for classification tasks, typically using features combined with linear weights to predict discrete labels.
  • D. LogisticRegression
    LogisticRegression is a scikit-learn machine learning estimator that models the probability of class membership using a linear decision boundary with logistic (sigmoid) or related link functions.
  • E. TensorFlow Estimators
    TensorFlow Estimators are a high-level TensorFlow API that simplifies building, training, and deploying machine learning models with standardized workflows and production-ready features.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d23cf08190925510344fa36f57 completed April 19, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01d283ddbc8190b0f8d710e2b334fe completed May 11, 2026, 12:58 p.m.
NEDg Description generation batch_6a01d328a3308190b18bf011a1a1d30b completed May 11, 2026, 1:01 p.m.
NED2 Entity disambiguation (via description) batch_6a01d3ca97b88190800530c80bd5dff0 completed May 11, 2026, 1:04 p.m.
Created at: April 10, 2026, 5:49 a.m.