Triple

T16736662
Position Surface form Disambiguated ID Type / Status
Subject Andrew J. Majda E406734 entity
Predicate familyName P18 FINISHED
Object Majda
Majda is a surname most notably associated with Andrew J. Majda, an influential American mathematician known for his work in applied mathematics and partial differential equations.
 E1231041 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: Majda | Statement: [Andrew J. Majda, familyName, Majda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Majda
Context triple: [Andrew J. Majda, familyName, Majda]
  • A. Julijana
    Julijana is a feminine given name, commonly used in Slavic countries, that corresponds to the name Juliana in other languages.
  • B. Nadiža
    Nadiža is a river in the western Balkans, known for its clear waters and scenic course through the mountainous border region between Slovenia and Italy.
  • C. Emilija
    Emilija is a feminine given name commonly used in various Slavic and Baltic countries, equivalent to Emilia or Emily in English.
  • D. Marija
    Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
  • E. Dáša
    Dáša is a common Czech and Slovak feminine given name, typically used as a diminutive form of Dagmar.
  • 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: Majda
Triple: [Andrew J. Majda, familyName, Majda]
Generated description
Majda is a surname most notably associated with Andrew J. Majda, an influential American mathematician known for his work in applied mathematics and partial differential equations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Majda
Target entity description: Majda is a surname most notably associated with Andrew J. Majda, an influential American mathematician known for his work in applied mathematics and partial differential equations.
  • A. Julijana
    Julijana is a feminine given name, commonly used in Slavic countries, that corresponds to the name Juliana in other languages.
  • B. Nadiža
    Nadiža is a river in the western Balkans, known for its clear waters and scenic course through the mountainous border region between Slovenia and Italy.
  • C. Emilija
    Emilija is a feminine given name commonly used in various Slavic and Baltic countries, equivalent to Emilia or Emily in English.
  • D. Marija
    Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
  • E. Dáša
    Dáša is a common Czech and Slovak feminine given name, typically used as a diminutive form of Dagmar.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e39c3a86848190a03f243dd1bdb899 completed April 18, 2026, 2:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d4ea8208190aed0a4014a10d120 completed May 10, 2026, 2:59 p.m.
NEDg Description generation batch_6a009ed297488190a20558efb9f91a55 completed May 10, 2026, 3:05 p.m.
NED2 Entity disambiguation (via description) batch_6a009f460010819086cfd7a7d74cb435 completed May 10, 2026, 3:07 p.m.
Created at: April 10, 2026, 5:20 a.m.