Triple

T1282530
Position Surface form Disambiguated ID Type / Status
Subject Clémentine E27357 entity
Predicate relatedName P3889 FINISHED
Object Clemence
Clemence is a given name of French origin, related to the name Clémentine and typically associated with the virtue of mercy or gentleness.
 E27357 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: Clemence | Statement: [Clémentine, relatedName, Clemence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Clemence
Context triple: [Clémentine, relatedName, Clemence]
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • C. Marguerite De La Motte
    Marguerite De La Motte was an American silent film actress best known for her leading roles in early 1920s adventure and drama films.
  • D. Camille Lefèvre
    Camille Lefèvre was a Swiss architect best known for co-designing the Palais des Nations, the former League of Nations headquarters in Geneva.
  • E. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • 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: Clemence
Triple: [Clémentine, relatedName, Clemence]
Generated description
Clemence is a given name of French origin, related to the name Clémentine and typically associated with the virtue of mercy or gentleness.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Clemence
Target entity description: Clemence is a given name of French origin, related to the name Clémentine and typically associated with the virtue of mercy or gentleness.
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Clémentine chosen
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • C. Marguerite De La Motte
    Marguerite De La Motte was an American silent film actress best known for her leading roles in early 1920s adventure and drama films.
  • D. Camille Lefèvre
    Camille Lefèvre was a Swiss architect best known for co-designing the Palais des Nations, the former League of Nations headquarters in Geneva.
  • E. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b47be08190828a1c0a11d94ce8 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad0e6027448190b10c65bcafe9fedf completed March 8, 2026, 5:51 a.m.
NEDg Description generation batch_69ad100fc7108190bf5211fb5817ca5f completed March 8, 2026, 5:58 a.m.
NED2 Entity disambiguation (via description) batch_69ad105a9bcc8190ba6d14df99ff2a7a completed March 8, 2026, 5:59 a.m.
Created at: March 1, 2026, 7:50 p.m.