Triple

T17841237
Position Surface form Disambiguated ID Type / Status
Subject Jong Wook Kim E445531 entity
Predicate notableWork P4 FINISHED
Object CLIP — NE NERFINISHED

How this triple was built (3 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: CLIP | Statement: [Jong Wook Kim, notableWork, CLIP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CLIP
Context triple: [Jong Wook Kim, notableWork, CLIP]
  • A. CLIP
    CLIP is an OpenAI model that learns joint representations of images and text, enabling tasks like zero-shot image classification and natural language-based image retrieval.
  • B. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • C. VisionEncoderDecoderModel
    VisionEncoderDecoderModel is a Hugging Face Transformers architecture that combines a vision encoder with a text decoder to perform tasks like image captioning and visual question answering.
  • D. ViT
    ViT (Vision Transformer) is a deep learning model architecture that applies the transformer framework to image recognition tasks by treating images as sequences of patches.
  • E. INTERPOL Diffusion
    INTERPOL Diffusion is a decentralized alert mechanism used within the INTERPOL network to rapidly share information about wanted persons, threats, or criminal activity among selected member countries.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CLIP
Target entity description: CLIP is an AI model developed by OpenAI that learns visual concepts from natural language supervision, enabling it to understand and relate images and text in a unified way.
  • A. CLIP chosen
    CLIP is an OpenAI model that learns joint representations of images and text, enabling tasks like zero-shot image classification and natural language-based image retrieval.
  • B. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • C. VisionEncoderDecoderModel
    VisionEncoderDecoderModel is a Hugging Face Transformers architecture that combines a vision encoder with a text decoder to perform tasks like image captioning and visual question answering.
  • D. ViT
    ViT (Vision Transformer) is a deep learning model architecture that applies the transformer framework to image recognition tasks by treating images as sequences of patches.
  • E. INTERPOL Diffusion
    INTERPOL Diffusion is a decentralized alert mechanism used within the INTERPOL network to rapidly share information about wanted persons, threats, or criminal activity among selected member countries.
  • F. None of above.

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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2b2ea08190926ec0cf01285833 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.