Triple

T849059
Position Surface form Disambiguated ID Type / Status
Subject Tony Wu E18341 entity
Predicate memberOf P10 FINISHED
Object xAI technical team E3339 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: xAI technical team | Statement: [Tony Wu, memberOf, xAI technical team]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: xAI technical team
Context triple: [Tony Wu, memberOf, xAI technical team]
  • A. xAI chosen
    xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
  • B. Element AI
    Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
  • C. Team KAIST
    Team KAIST is a South Korean robotics research team from the Korea Advanced Institute of Science and Technology renowned for developing advanced humanoid robots and achieving top honors in international robotics competitions.
  • D. ChatGPT Team
    ChatGPT Team is a subscription plan designed for collaborative use, allowing multiple users within an organization or group to share access to advanced ChatGPT features and management tools.
  • E. AIST
    AIST is a professional association that supports the global iron and steel industry through technology advancement, education, and networking among industry professionals.
  • 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_69a4938b04208190b82e1df6b572c548 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac1fac3481909cba7070ce31a9b3 completed March 1, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a792a0666c8190bfc9166d45b4e867 completed March 4, 2026, 2:02 a.m.
Created at: March 1, 2026, 7:38 p.m.