Triple

T2236430
Position Surface form Disambiguated ID Type / Status
Subject Richard Ben-Veniste E49291 entity
Predicate familyName P18 FINISHED
Object Ben-Veniste
Ben-Veniste is the surname of Richard Ben-Veniste, an American lawyer known for his roles in high-profile U.S. government investigations.
E248474 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: Ben-Veniste | Statement: [Richard Ben-Veniste, familyName, Ben-Veniste]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben-Veniste
Context triple: [Richard Ben-Veniste, familyName, Ben-Veniste]
  • A. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • B. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • C. Val Veny
    Val Veny is a scenic alpine valley near Courmayeur in Italy’s Aosta Valley, known for its dramatic views of Mont Blanc, hiking trails, and natural landscapes.
  • D. Vivanco
    Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
  • E. Tournier
    Tournier is a surname of French origin, sometimes used as a variant of the English surname Turner.
  • 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: Ben-Veniste
Triple: [Richard Ben-Veniste, familyName, Ben-Veniste]
Generated description
Ben-Veniste is the surname of Richard Ben-Veniste, an American lawyer known for his roles in high-profile U.S. government investigations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ben-Veniste
Target entity description: Ben-Veniste is the surname of Richard Ben-Veniste, an American lawyer known for his roles in high-profile U.S. government investigations.
  • A. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • B. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • C. Val Veny
    Val Veny is a scenic alpine valley near Courmayeur in Italy’s Aosta Valley, known for its dramatic views of Mont Blanc, hiking trails, and natural landscapes.
  • D. Vivanco
    Vivanco is a Spanish-language surname of likely Iberian origin borne by various notable individuals.
  • E. Tournier
    Tournier is a surname of French origin, sometimes used as a variant of the English surname Turner.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc09573848190bf91eddcc2fa0061 completed March 7, 2026, 6:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b08c5248190924a28f4c1bd0e2c completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6c5cb33481909261f7010e8e21a6 completed March 9, 2026, 6:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae6cd61e808190aefca4d4aa1f8e39 completed March 9, 2026, 6:46 a.m.
Created at: March 4, 2026, 7:47 p.m.