Triple

T188827
Position Surface form Disambiguated ID Type / Status
Subject Pierre E3672 entity
Predicate hasVariant P455 FINISHED
Object Pierrick
Pierrick is a French given name, commonly used as a diminutive or regional variant of Pierre.
 E3672 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: Pierrick | Statement: [Pierre, hasVariant, Pierrick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pierrick
Context triple: [Pierre, hasVariant, Pierrick]
  • A. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • B. Georges
    Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
  • C. 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.
  • D. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • E. André
    André is a given name of French origin commonly used in various languages as a form of "Andrew."
  • 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: Pierrick
Triple: [Pierre, hasVariant, Pierrick]
Generated description
Pierrick is a French given name, commonly used as a diminutive or regional variant of Pierre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pierrick
Target entity description: Pierrick is a French given name, commonly used as a diminutive or regional variant of Pierre.
  • A. Pierre chosen
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • B. Georges
    Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
  • C. 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.
  • D. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • E. André
    André is a given name of French origin commonly used in various languages as a form of "Andrew."
  • F. None of above.

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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a2594abeec8190a48f36817e647fcd completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a338e55004819096a8cc1bfec7a225 completed Feb. 28, 2026, 6:50 p.m.
NEDg Description generation batch_69a33cc26d94819091e6d73074babedb completed Feb. 28, 2026, 7:06 p.m.
NED2 Entity disambiguation (via description) batch_69a33d2fa67081909b9f88606b18ba93 completed Feb. 28, 2026, 7:08 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.