Triple

T8251179
Position Surface form Disambiguated ID Type / Status
Subject Resnick E192958 entity
Predicate hasNotableBearer P458 FINISHED
Object Martin Resnick
Martin Resnick is an individual notable enough to be recognized as a prominent bearer of the surname Resnick.
 E731103 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: Martin Resnick | Statement: [Resnick, hasNotableBearer, Martin Resnick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Martin Resnick
Context triple: [Resnick, hasNotableBearer, Martin Resnick]
  • A. David Weinberg
    David Weinberg is a name shared by multiple notable individuals, including professionals in fields such as science, academia, and the arts.
  • B. David Lanzenberg
    David Lanzenberg is a film cinematographer known for his work on feature films such as "Paper Towns."
  • C. Jeremy Shamos
    Jeremy Shamos is an American stage and screen actor known for his work on Broadway and in film and television.
  • D. Robert Scheifler
    Robert Scheifler is a computer scientist best known for leading the development of the X Window System at MIT.
  • E. Michael Moscovitz
    Michael Moscovitz is a central character in Meg Cabot’s "The Princess Diaries" series, known as Mia Thermopolis’s witty, musically inclined romantic interest and eventual boyfriend.
  • 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: Martin Resnick
Triple: [Resnick, hasNotableBearer, Martin Resnick]
Generated description
Martin Resnick is an individual notable enough to be recognized as a prominent bearer of the surname Resnick.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Martin Resnick
Target entity description: Martin Resnick is an individual notable enough to be recognized as a prominent bearer of the surname Resnick.
  • A. David Weinberg
    David Weinberg is a name shared by multiple notable individuals, including professionals in fields such as science, academia, and the arts.
  • B. David Lanzenberg
    David Lanzenberg is a film cinematographer known for his work on feature films such as "Paper Towns."
  • C. Jeremy Shamos
    Jeremy Shamos is an American stage and screen actor known for his work on Broadway and in film and television.
  • D. Robert Scheifler
    Robert Scheifler is a computer scientist best known for leading the development of the X Window System at MIT.
  • E. Michael Moscovitz
    Michael Moscovitz is a central character in Meg Cabot’s "The Princess Diaries" series, known as Mia Thermopolis’s witty, musically inclined romantic interest and eventual boyfriend.
  • 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78c935408190b9196a849a8d3a3e completed March 31, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce024f17a8819083f96ce8494fbb58 completed April 2, 2026, 5:44 a.m.
NEDg Description generation batch_69ce077d8af0819082a7ea67a2c11ddd completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce082078108190867044f45bc0a806 completed April 2, 2026, 6:09 a.m.
Created at: March 30, 2026, 5:48 p.m.