Triple

T11063247
Position Surface form Disambiguated ID Type / Status
Subject Future World E261559 entity
Predicate featuredAttraction P5121 FINISHED
Object Innoventions E231048 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: Innoventions | Statement: [Future World, featuredAttraction, Innoventions]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innoventions
Context triple: [Future World, featuredAttraction, Innoventions]
  • A. Innoventions chosen
    Innoventions was an interactive exhibit pavilion at Epcot in Walt Disney World that showcased emerging technologies and hands-on science displays.
  • B. Nova Innovation
    Nova Innovation is a renewable energy company specializing in the design, manufacture, and deployment of tidal energy turbines and projects.
  • C. Innogen
    Innogen is the original name of Imogen, the virtuous and wronged heroine of William Shakespeare’s play "Cymbeline."
  • D. Invetech
    Invetech is a technology and product development company specializing in designing and engineering innovative medical and life science solutions.
  • E. Innosight
    Innosight is a strategy and innovation consulting firm co-founded by disruptive innovation theorist Clayton Christensen, known for helping organizations navigate transformational growth and change.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798ed07f88190bf501d9f63386ada completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c887d2148190b19c91b6eb548494 completed April 18, 2026, 6:08 p.m.
Created at: April 8, 2026, 9:26 p.m.