Triple

T8433156
Position Surface form Disambiguated ID Type / Status
Subject Scarlet Witch E199163 entity
Predicate spouse P13 FINISHED
Object Vision E123985 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: Vision | Statement: [Scarlet Witch, spouse, Vision]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vision
Context triple: [Scarlet Witch, spouse, Vision]
  • A. Vision chosen
    Vision is a powerful, synthetically created superhero in the Marvel universe known for his android body, advanced intellect, and moral complexity.
  • B. Vision
    Vision is Apple’s mixed-reality product line centered on advanced spatial computing headsets like the Apple Vision Pro.
  • C. VIS
    VIS is the IATA airport code for Visalia Municipal Airport in Visalia, California, United States.
  • D. See
    See is a post-apocalyptic science fiction television series in which a future human society has lost the sense of sight, leading to unique cultural and power struggles.
  • E. Vision and Design
    Vision and Design is an influential collection of art criticism essays by Roger Fry that helped shape modernist art theory and appreciation in the early 20th century.
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a74d948190abd76e7a6efb42ec completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d673ed48190abf765c203ed2a0f completed April 2, 2026, 7:40 a.m.
Created at: March 30, 2026, 6:07 p.m.