Triple

T3165201
Position Surface form Disambiguated ID Type / Status
Subject Philippe Beaudoin E66194 entity
Predicate coFounded P104 FINISHED
Object Element AI E8584 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: Element AI | Statement: [Philippe Beaudoin, coFounded, Element AI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Element AI
Context triple: [Philippe Beaudoin, coFounded, Element AI]
  • A. Element AI chosen
    Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
  • B. Einstein AI
    Einstein AI is Salesforce’s integrated artificial intelligence platform that powers predictive analytics, automation, and intelligent insights across its CRM ecosystem.
  • C. OpenAI
    OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
  • D. Sparx
    Sparx is the loyal dragonfly companion and health indicator who follows Spyro throughout the Spyro the Dragon video game series.
  • E. Meta AI
    Meta AI is Meta Platforms’ artificial intelligence division, responsible for developing large-scale AI models, research, and consumer-facing tools like the Meta AI assistant integrated across its apps and services.
  • 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_69ad8585d7988190af37365331093ccd completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6424ee48190a29891ffbbc3811d completed March 8, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28e4cdd2c8190a4b09e968b9d39be completed March 12, 2026, 9:58 a.m.
Created at: March 8, 2026, 3:06 p.m.