Triple

T2835240
Position Surface form Disambiguated ID Type / Status
Subject Picasso at the Lapin Agile E62332 entity
Predicate mainCharacter P1183 FINISHED
Object Germaine
Germaine is a central character in Steve Martin’s play "Picasso at the Lapin Agile," serving as the sharp-witted barmaid who anchors the action in the Parisian café.
 E302681 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: Germaine | Statement: [Picasso at the Lapin Agile, mainCharacter, Germaine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Germaine
Context triple: [Picasso at the Lapin Agile, mainCharacter, Germaine]
  • A. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • B. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • C. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • D. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • E. Geraldine
    Geraldine is a feminine given name of Germanic origin that has been borne by various notable figures, including actress Geraldine Chaplin.
  • 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: Germaine
Triple: [Picasso at the Lapin Agile, mainCharacter, Germaine]
Generated description
Germaine is a central character in Steve Martin’s play "Picasso at the Lapin Agile," serving as the sharp-witted barmaid who anchors the action in the Parisian café.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Germaine
Target entity description: Germaine is a central character in Steve Martin’s play "Picasso at the Lapin Agile," serving as the sharp-witted barmaid who anchors the action in the Parisian café.
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Antoinette
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • C. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • D. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • E. Geraldine
    Geraldine is a feminine given name of Germanic origin that has been borne by various notable figures, including actress Geraldine Chaplin.
  • 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeea881481908d759c72798a50fb completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8c45c548190ac67b94a845cc730 completed March 10, 2026, 9:47 a.m.
NEDg Description generation batch_69afe9a000c4819085be1794bff0d506 completed March 10, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_69b0010b0ddc8190b4bfb18448f88077 completed March 10, 2026, 11:31 a.m.
Created at: March 6, 2026, 10:01 p.m.