Triple

T3918453
Position Surface form Disambiguated ID Type / Status
Subject Yannick Nézet-Séguin E88901 entity
Predicate givenName P17 FINISHED
Object Yannick
Yannick is a masculine given name of Breton origin, commonly used in French-speaking regions and borne by figures such as conductor Yannick Nézet-Séguin.
 E399050 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: Yannick | Statement: [Yannick Nézet-Séguin, givenName, Yannick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yannick
Context triple: [Yannick Nézet-Séguin, givenName, Yannick]
  • A. Yann
    Yann is the given name of Yann LeCun, a pioneering computer scientist known for his foundational work in deep learning and convolutional neural networks.
  • B. Baptiste
    Baptiste is a British crime drama television series centered on the character of detective Julien Baptiste, a spin-off from the series "The Missing."
  • C. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • D. Yves
    Yves is a masculine given name of French origin commonly used in Francophone countries.
  • E. Stéphane
    Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
  • 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: Yannick
Triple: [Yannick Nézet-Séguin, givenName, Yannick]
Generated description
Yannick is a masculine given name of Breton origin, commonly used in French-speaking regions and borne by figures such as conductor Yannick Nézet-Séguin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yannick
Target entity description: Yannick is a masculine given name of Breton origin, commonly used in French-speaking regions and borne by figures such as conductor Yannick Nézet-Séguin.
  • A. Yann
    Yann is the given name of Yann LeCun, a pioneering computer scientist known for his foundational work in deep learning and convolutional neural networks.
  • B. Baptiste
    Baptiste is a British crime drama television series centered on the character of detective Julien Baptiste, a spin-off from the series "The Missing."
  • C. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • D. Yves
    Yves is a masculine given name of French origin commonly used in Francophone countries.
  • E. Stéphane
    Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed59485c819095c58edd053e3401 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5286830d08190bd6e583360136342 completed March 14, 2026, 9:20 a.m.
NEDg Description generation batch_69b5293b41748190929665970712707a completed March 14, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_69b529e9080481908ff0ec30b295cfc3 completed March 14, 2026, 9:27 a.m.
Created at: March 9, 2026, 3:22 p.m.