Triple

T3790678
Position Surface form Disambiguated ID Type / Status
Subject Jean-Marie Lehn E89638 entity
Predicate familyName P18 FINISHED
Object Lehn
Lehn is the surname of Jean-Marie Lehn, a Nobel Prize–winning French chemist renowned for pioneering the field of supramolecular chemistry.
E388810 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: Lehn | Statement: [Jean-Marie Lehn, familyName, Lehn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lehn
Context triple: [Jean-Marie Lehn, familyName, Lehn]
  • A. Löwenthal
    Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
  • B. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • C. Biesenthal
    Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
  • D. Wertheim
    Wertheim is a German-origin surname borne by various notable individuals in fields such as finance, philanthropy, and the arts.
  • E. Heurich
    Heurich is a German surname most notably associated with Christian Heurich, a prominent brewer and businessman in Washington, D.C.
  • 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: Lehn
Triple: [Jean-Marie Lehn, familyName, Lehn]
Generated description
Lehn is the surname of Jean-Marie Lehn, a Nobel Prize–winning French chemist renowned for pioneering the field of supramolecular chemistry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lehn
Target entity description: Lehn is the surname of Jean-Marie Lehn, a Nobel Prize–winning French chemist renowned for pioneering the field of supramolecular chemistry.
  • A. Löwenthal
    Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
  • B. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • C. Biesenthal
    Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
  • D. Wertheim
    Wertheim is a German-origin surname borne by various notable individuals in fields such as finance, philanthropy, and the arts.
  • E. Heurich
    Heurich is a German surname most notably associated with Christian Heurich, a prominent brewer and businessman in Washington, D.C.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee7687c4481908d5e6988e2638b68 completed March 9, 2026, 3:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f055e3988190a1b3633e390c0d6f completed March 14, 2026, 5:21 a.m.
NEDg Description generation batch_69b4f2094c988190a812194ef5598cdf completed March 14, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_69b4f26aee948190b95c94801f0959ec completed March 14, 2026, 5:30 a.m.
Created at: March 9, 2026, 3:15 p.m.