Triple

T197601
Position Surface form Disambiguated ID Type / Status
Subject Mila – Quebec Artificial Intelligence Institute E4031 entity
Predicate alsoKnownAs P39 FINISHED
Object Mila
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
 E28783 NE FINISHED

How this triple was built (4 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: Mila | Statement: [Mila – Quebec Artificial Intelligence Institute, alsoKnownAs, Mila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mila
Context triple: [Mila – Quebec Artificial Intelligence Institute, alsoKnownAs, Mila]
  • A. Michal
    Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
  • B. Anastasia Shubskaya
    Anastasia Shubskaya is a Russian model and film producer best known as the wife of NHL star Alex Ovechkin.
  • C. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • D. Sophia
    Sophia of the Palatinate was a 17th-century German princess and Electress of Hanover, best known as the mother of King George I of Great Britain and a key figure in the Protestant succession to the British throne.
  • E. Hilda
    Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mila
Triple: [Mila – Quebec Artificial Intelligence Institute, alsoKnownAs, Mila]
Generated description
Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mila
Target entity description: Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
  • A. Michal
    Michal is a biblical figure, a daughter of King Saul who became the first wife of King David in the Hebrew Bible.
  • B. Anastasia Shubskaya
    Anastasia Shubskaya is a Russian model and film producer best known as the wife of NHL star Alex Ovechkin.
  • C. Maia
    Maia is a figure from Greek mythology, one of the Pleiades and the mother of the god Hermes.
  • D. Sophia
    Sophia of the Palatinate was a 17th-century German princess and Electress of Hanover, best known as the mother of King George I of Great Britain and a key figure in the Protestant succession to the British throne.
  • E. Hilda
    Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
  • F. None of above. chosen

Provenance (5 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_69a254bca59881909a15e1496f1508c7 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25bc96aa081908ef74c9827c9aa48 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a352734730819091211462a23204ea completed Feb. 28, 2026, 8:39 p.m.
NEDg Description generation batch_69a355f97db8819080665fa585955380 completed Feb. 28, 2026, 8:54 p.m.
NED2 Entity disambiguation (via description) batch_69a3567126dc81909853cb7dab5609c1 completed Feb. 28, 2026, 8:56 p.m.
Created at: Feb. 28, 2026, 2:44 a.m.