Triple

T3542951
Position Surface form Disambiguated ID Type / Status
Subject ResNet E74928 entity
Predicate developedBy P73 FINISHED
Object Xiangyu Zhang
Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
 E367296 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: Xiangyu Zhang | Statement: [ResNet, developedBy, Xiangyu Zhang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Xiangyu Zhang
Context triple: [ResNet, developedBy, Xiangyu Zhang]
  • A. Xiaodong Chen
    Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
  • B. Yuhuai Wu
    Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
  • C. Jun-Yan Zhu
    Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
  • D. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • E. Wei Liu
    Wei Liu is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work on object detection.
  • 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: Xiangyu Zhang
Triple: [ResNet, developedBy, Xiangyu Zhang]
Generated description
Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Xiangyu Zhang
Target entity description: Xiangyu Zhang is a computer vision and deep learning researcher known for his contributions to convolutional neural network architectures and large-scale visual recognition.
  • A. Xiaodong Chen
    Xiaodong Chen is a prominent materials scientist and nanotechnology researcher who serves as editor-in-chief of the journal ACS Nano.
  • B. Yuhuai Wu
    Yuhuai Wu is an AI researcher and entrepreneur known for his work on large language models and as a member of Elon Musk’s xAI team.
  • C. Jun-Yan Zhu
    Jun-Yan Zhu is a computer scientist and researcher known for his influential work in computer vision and generative models, particularly in image-to-image translation.
  • D. Xindong Wu
    Xindong Wu is a prominent computer scientist known for his influential contributions to data mining and knowledge discovery research.
  • E. Wei Liu
    Wei Liu is a computer scientist and researcher known for his contributions to deep learning and computer vision, including influential work on object detection.
  • 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_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.
NEDg Description generation batch_69b38cb6a2188190b68f4903144a0e51 completed March 13, 2026, 4:04 a.m.
NED2 Entity disambiguation (via description) batch_69b39062a10c8190bc227c02cf4f3ab1 completed March 13, 2026, 4:19 a.m.
Created at: March 8, 2026, 3:20 p.m.