Triple

T996249
Position Surface form Disambiguated ID Type / Status
Subject Dominique Strauss-Kahn E21501 entity
Predicate givenName P17 FINISHED
Object Dominique
Dominique is a French given name commonly used for both males and females, notably borne by figures such as former IMF chief Dominique Strauss-Kahn.
E134253 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: Dominique | Statement: [Dominique Strauss-Kahn, givenName, Dominique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dominique
Context triple: [Dominique Strauss-Kahn, givenName, Dominique]
  • A. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • B. 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.
  • C. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • D. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • E. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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: Dominique
Triple: [Dominique Strauss-Kahn, givenName, Dominique]
Generated description
Dominique is a French given name commonly used for both males and females, notably borne by figures such as former IMF chief Dominique Strauss-Kahn.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dominique
Target entity description: Dominique is a French given name commonly used for both males and females, notably borne by figures such as former IMF chief Dominique Strauss-Kahn.
  • A. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • B. 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.
  • C. Micheline
    Micheline is a feminine given name of French origin, commonly used in French-speaking countries.
  • D. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • E. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4df6dcc819084a7c0a50637a2c2 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66179f908190b3f0144d1ee91a1c completed March 7, 2026, 5:53 p.m.
NEDg Description generation batch_69ac66f0e874819092d51913f08905d4 completed March 7, 2026, 5:57 p.m.
NED2 Entity disambiguation (via description) batch_69ac676cb9a08190a83d47de80126677 completed March 7, 2026, 5:59 p.m.
Created at: March 1, 2026, 7:41 p.m.