Triple

T188828
Position Surface form Disambiguated ID Type / Status
Subject Pierre E3672 entity
Predicate hasDiminutive P456 FINISHED
Object Pierrot
Pierrot is a traditional stock character from French pantomime and commedia dell’arte, typically portrayed as a sad, white-faced clown in loose white clothing.
 E23980 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: Pierrot | Statement: [Pierre, hasDiminutive, Pierrot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pierrot
Context triple: [Pierre, hasDiminutive, Pierrot]
  • 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. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • C. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • D. Don Juan
    Don Juan is a long satirical narrative poem by Lord Byron that humorously reimagines the legendary libertine as a naïve young man swept through a series of romantic and political adventures.
  • E. 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."
  • 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: Pierrot
Triple: [Pierre, hasDiminutive, Pierrot]
Generated description
Pierrot is a traditional stock character from French pantomime and commedia dell’arte, typically portrayed as a sad, white-faced clown in loose white clothing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pierrot
Target entity description: Pierrot is a traditional stock character from French pantomime and commedia dell’arte, typically portrayed as a sad, white-faced clown in loose white clothing.
  • 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. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • C. Madam
    "Madam" is a formal term of address for a woman, often used to show respect or politeness in social, professional, or official contexts.
  • D. Don Juan
    Don Juan is a long satirical narrative poem by Lord Byron that humorously reimagines the legendary libertine as a naïve young man swept through a series of romantic and political adventures.
  • E. 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."
  • 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_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_69a305e511a08190a560125ed3839a0c completed Feb. 28, 2026, 3:12 p.m.
NEDg Description generation batch_69a30679b0648190975dcfaf4f9846bf completed Feb. 28, 2026, 3:15 p.m.
NED2 Entity disambiguation (via description) batch_69a306e6ce6c8190a77d42643914b03a completed Feb. 28, 2026, 3:16 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.