Triple

T1394129
Position Surface form Disambiguated ID Type / Status
Subject René E30626 entity
Predicate hasVariant P455 FINISHED
Object Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
 E175041 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: Renée | Statement: [René, hasVariant, Renée]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Renée
Context triple: [René, hasVariant, Renée]
  • A. 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.
  • B. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • C. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • D. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • E. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • 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: Renée
Triple: [René, hasVariant, Renée]
Generated description
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Renée
Target entity description: Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • A. 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.
  • B. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • C. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • D. Marie
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • E. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • 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_69a498fd4e408190bd73eca30ea9754c completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c37cd99081908d16014e0b99992d completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293ab8508190ac321c898cd3df39 completed March 8, 2026, 7:46 a.m.
NEDg Description generation batch_69ad2d23e14881909fc5a4d89c0b74f4 completed March 8, 2026, 8:02 a.m.
NED2 Entity disambiguation (via description) batch_69ad2ded1d548190b0c51c460a751017 completed March 8, 2026, 8:06 a.m.
Created at: March 1, 2026, 7:59 p.m.