Triple

T3233130
Position Surface form Disambiguated ID Type / Status
Subject Hannelore Kohl E67788 entity
Predicate givenName P17 FINISHED
Object Klara
Klara is the given first name of Hannelore Kohl, the late wife of former German Chancellor Helmut Kohl.
 E339402 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: Klara | Statement: [Hannelore Kohl, givenName, Klara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Klara
Context triple: [Hannelore Kohl, givenName, Klara]
  • A. Clara
    Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
  • B. Clara
    Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
  • C. Klara Dan
    Klara Dan was a Hungarian-American mathematician and computer programmer known for her pioneering work on early digital computers alongside her husband, John von Neumann.
  • D. Valli
    Valli is a Hindu goddess and one of the two principal consorts of the god Kartikeya (Murugan), especially revered in South Indian and Tamil traditions.
  • E. Momo
    Momo is the young, troubled Jewish boy who forms a transformative friendship with the elderly Muslim shopkeeper in Éric-Emmanuel Schmitt’s novella *Monsieur Ibrahim and the Flowers of the Koran*.
  • 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: Klara
Triple: [Hannelore Kohl, givenName, Klara]
Generated description
Klara is the given first name of Hannelore Kohl, the late wife of former German Chancellor Helmut Kohl.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Klara
Target entity description: Klara is the given first name of Hannelore Kohl, the late wife of former German Chancellor Helmut Kohl.
  • A. Clara
    Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
  • B. Clara
    Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
  • C. Klara Dan
    Klara Dan was a Hungarian-American mathematician and computer programmer known for her pioneering work on early digital computers alongside her husband, John von Neumann.
  • D. Valli
    Valli is a Hindu goddess and one of the two principal consorts of the god Kartikeya (Murugan), especially revered in South Indian and Tamil traditions.
  • E. Momo
    Momo is the young, troubled Jewish boy who forms a transformative friendship with the elderly Muslim shopkeeper in Éric-Emmanuel Schmitt’s novella *Monsieur Ibrahim and the Flowers of the Koran*.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaedb718c8190aae12f763033713a completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2773b494c8190a2c0c5042e8eaa55 completed March 12, 2026, 8:20 a.m.
NEDg Description generation batch_69b27844c6708190ac61f00a74a2ef27 completed March 12, 2026, 8:24 a.m.
NED2 Entity disambiguation (via description) batch_69b27911ff1481908a36f279a871c510 completed March 12, 2026, 8:28 a.m.
Created at: March 8, 2026, 3:08 p.m.