Triple

T3542995
Position Surface form Disambiguated ID Type / Status
Subject ResNet E74928 entity
Predicate implementationAvailableIn P22535 FINISHED
Object MXNet E234123 NE FINISHED

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: MXNet | Statement: [ResNet, implementationAvailableIn, MXNet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MXNet
Context triple: [ResNet, implementationAvailableIn, MXNet]
  • A. MXNet chosen
    MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
  • B. Theano
    Theano is an open-source numerical computation library for Python that allows efficient definition, optimization, and evaluation of mathematical expressions, particularly those involving multi-dimensional arrays, and was widely used as a backend for deep learning frameworks.
  • C. TensorFlow
    TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
  • D. Microsoft Cognitive Toolkit
    Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning framework developed by Microsoft for building, training, and deploying neural networks at scale.
  • E. PyTorch
    PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85d274cc8190ab59c97298a1cfbf completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbf752dd481909226044ffe595338 completed March 8, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bdd0cb4819086119b54c2708850 completed March 13, 2026, 4 a.m.
Created at: March 8, 2026, 3:20 p.m.