Triple

T10279666
Position Surface form Disambiguated ID Type / Status
Subject Natalia Bryant E241063 entity
Predicate employer P7 FINISHED
Object IMG Models E568749 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: IMG Models | Statement: [Natalia Bryant, employer, IMG Models]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: IMG Models
Context triple: [Natalia Bryant, employer, IMG Models]
  • A. IMG chosen
    IMG is a global sports, events, and talent management company known for representing athletes and models and producing major sporting and fashion events.
  • B. 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.
  • C. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • D. Mikros Image
    Mikros Image is a visual effects and animation studio known for its work on feature films and animated projects.
  • E. The Models
    The Models is a large post-Impressionist painting by Georges Seurat that depicts three nude female figures in a studio, showcasing his pointillist technique and exploration of modern life.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d29fdf2c819099dd581deac08cf2 completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f82f16688190b1c6b80e424bd552 completed April 9, 2026, 12:51 a.m.
Created at: April 6, 2026, 11:38 a.m.