Triple

T20205594
Position Surface form Disambiguated ID Type / Status
Subject Feodor Lynen E493341 entity
Predicate familyName P18 FINISHED
Object Lynen
Lynen is a German surname most notably associated with Nobel Prize–winning biochemist Feodor Lynen.
 E1418273 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: Lynen | Statement: [Feodor Lynen, familyName, Lynen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lynen
Context triple: [Feodor Lynen, familyName, Lynen]
  • A. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • B. Landé
    Landé is a German surname most notably associated with physicist Alfred Landé, known for his contributions to quantum theory and atomic physics.
  • C. Lennik
    Lennik is a municipality in the Flemish Brabant province of Belgium, known for its rural character and historic castle of Gaasbeek.
  • D. Beckstein
    Beckstein is a wine-producing village and district of the town Lauda-Königshofen in the Main-Tauber region of Baden-Württemberg, Germany.
  • E. Kniphausen
    Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
  • 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: Lynen
Triple: [Feodor Lynen, familyName, Lynen]
Generated description
Lynen is a German surname most notably associated with Nobel Prize–winning biochemist Feodor Lynen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lynen
Target entity description: Lynen is a German surname most notably associated with Nobel Prize–winning biochemist Feodor Lynen.
  • A. Lyness
    Lyness is a small coastal village and former naval base on the island of Hoy in Orkney, Scotland.
  • B. Landé
    Landé is a German surname most notably associated with physicist Alfred Landé, known for his contributions to quantum theory and atomic physics.
  • C. Lennik
    Lennik is a municipality in the Flemish Brabant province of Belgium, known for its rural character and historic castle of Gaasbeek.
  • D. Beckstein
    Beckstein is a wine-producing village and district of the town Lauda-Königshofen in the Main-Tauber region of Baden-Württemberg, Germany.
  • E. Kniphausen
    Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d913c088190b80b251fba5c368f completed April 20, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0843ecd72c8190a605ccb8af032795 completed May 16, 2026, 10:16 a.m.
NEDg Description generation batch_6a0845193350819088523da3087fe421 completed May 16, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0845e241048190ba7fb657d4dca3d7 completed May 16, 2026, 10:24 a.m.
Created at: April 11, 2026, 11:38 p.m.