Triple

T13577465
Position Surface form Disambiguated ID Type / Status
Subject Derek de Solla Price Memorial Medal E324324 entity
Predicate notableRecipient P108 FINISHED
Object Michel Zitt
Michel Zitt is a prominent French scholar in scientometrics and research evaluation, recognized internationally for his influential contributions to the quantitative study of science and technology.
E1048259 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: Michel Zitt | Statement: [Derek de Solla Price Memorial Medal, notableRecipient, Michel Zitt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michel Zitt
Context triple: [Derek de Solla Price Memorial Medal, notableRecipient, Michel Zitt]
  • A. Michel Gill
    Michel Gill is an American actor best known for his roles in television series such as "House of Cards" and "The Dropout."
  • B. Michel Fessler
    Michel Fessler is a French screenwriter best known for co-writing the acclaimed nature documentary film "March of the Penguins."
  • C. Denis Douyon
    Denis Douyon is a researcher known for his scholarly work on the Dogon languages of Mali.
  • D. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • E. Michel Bizot
    Michel Bizot is a Paris Métro station in the 12th arrondissement, named after the 19th-century French general Michel Brice Bizot.
  • 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: Michel Zitt
Triple: [Derek de Solla Price Memorial Medal, notableRecipient, Michel Zitt]
Generated description
Michel Zitt is a prominent French scholar in scientometrics and research evaluation, recognized internationally for his influential contributions to the quantitative study of science and technology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Michel Zitt
Target entity description: Michel Zitt is a prominent French scholar in scientometrics and research evaluation, recognized internationally for his influential contributions to the quantitative study of science and technology.
  • A. Michel Gill
    Michel Gill is an American actor best known for his roles in television series such as "House of Cards" and "The Dropout."
  • B. Michel Fessler
    Michel Fessler is a French screenwriter best known for co-writing the acclaimed nature documentary film "March of the Penguins."
  • C. Denis Douyon
    Denis Douyon is a researcher known for his scholarly work on the Dogon languages of Mali.
  • D. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • E. Michel Bizot
    Michel Bizot is a Paris Métro station in the 12th arrondissement, named after the 19th-century French general Michel Brice Bizot.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb02de1988190af2d473973ecd529 completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bbbe3c08190a359dfe7c3c8f15c completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77641e5308190a75bcffeb9bfd7b4 completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f7791add908190af69b23a54eb7560 completed May 3, 2026, 4:34 p.m.
Created at: April 9, 2026, 9:48 p.m.