Triple

T2385677
Position Surface form Disambiguated ID Type / Status
Subject Martine McCutcheon E48816 entity
Predicate givenName P17 FINISHED
Object Martine
Martine is a feminine given name commonly used in French- and English-speaking countries.
 E260455 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: Martine | Statement: [Martine McCutcheon, givenName, Martine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Martine
Context triple: [Martine McCutcheon, givenName, Martine]
  • A. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • B. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • 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. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Valérie
    Valérie is a French feminine given name 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: Martine
Triple: [Martine McCutcheon, givenName, Martine]
Generated description
Martine is a feminine given name commonly used in French- and English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Martine
Target entity description: Martine is a feminine given name commonly used in French- and English-speaking countries.
  • A. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • B. Françoise
    Françoise is the given name of Louise de La Vallière, a 17th-century French noblewoman best known as a mistress of King Louis XIV.
  • 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. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Valérie
    Valérie is a French feminine given name 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc7d8a918819089a210e74e13be6e completed March 7, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8bae2ec8190962479832bf7762e completed March 9, 2026, 11:02 a.m.
NEDg Description generation batch_69aeab4258f88190a7a009d0fa501dd4 completed March 9, 2026, 11:13 a.m.
NED2 Entity disambiguation (via description) batch_69aeaba59cd08190981af351019b3e81 completed March 9, 2026, 11:14 a.m.
Created at: March 4, 2026, 7:57 p.m.