Triple

T14393359
Position Surface form Disambiguated ID Type / Status
Subject Jiawei Han E356897 entity
Predicate coAuthor P398 FINISHED
Object Micheline Kamber
Micheline Kamber is a computer scientist and co-author of the influential data mining textbook "Data Mining: Concepts and Techniques."
E1129311 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: Micheline Kamber | Statement: [Jiawei Han, coAuthor, Micheline Kamber]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Micheline Kamber
Context triple: [Jiawei Han, coAuthor, Micheline Kamber]
  • A. Micheline Winter
    Micheline Winter was the wife of renowned French filmmaker and actor Jacques Tati.
  • B. Micheline Ostermeyer
    Micheline Ostermeyer was a French athlete and concert pianist renowned for winning multiple track and field medals at the 1948 Olympic Games.
  • C. Michèle Méritz
    Michèle Méritz was a French actress known for her role in Claude Chabrol’s influential New Wave film "Le Beau Serge."
  • D. Hélène Cruppi
    Hélène Cruppi was the wife of French politician and lawyer Jean Cruppi, known primarily through her association with his public and political life.
  • E. Josette Contandin
    Josette Contandin is the daughter of famed French actor and comedian Fernandel.
  • 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: Micheline Kamber
Triple: [Jiawei Han, coAuthor, Micheline Kamber]
Generated description
Micheline Kamber is a computer scientist and co-author of the influential data mining textbook "Data Mining: Concepts and Techniques."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Micheline Kamber
Target entity description: Micheline Kamber is a computer scientist and co-author of the influential data mining textbook "Data Mining: Concepts and Techniques."
  • A. Micheline Winter
    Micheline Winter was the wife of renowned French filmmaker and actor Jacques Tati.
  • B. Micheline Ostermeyer
    Micheline Ostermeyer was a French athlete and concert pianist renowned for winning multiple track and field medals at the 1948 Olympic Games.
  • C. Michèle Méritz
    Michèle Méritz was a French actress known for her role in Claude Chabrol’s influential New Wave film "Le Beau Serge."
  • D. Hélène Cruppi
    Hélène Cruppi was the wife of French politician and lawyer Jean Cruppi, known primarily through her association with his public and political life.
  • E. Josette Contandin
    Josette Contandin is the daughter of famed French actor and comedian Fernandel.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de902b9acc8190817ffa848a76a880 completed April 14, 2026, 7:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bbfc6048190897f064a5686ebf8 completed May 9, 2026, 1:19 a.m.
NEDg Description generation batch_69fe8cfd57dc81909ba5789fefa0092c completed May 9, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_69fe8d955d2c819087bb42e644478fbe completed May 9, 2026, 1:27 a.m.
Created at: April 10, 2026, 1:16 a.m.