Triple

T19563576
Position Surface form Disambiguated ID Type / Status
Subject Rosemarie E489518 entity
Predicate hasDiminutive P456 FINISHED
Object Marie
Marie is a feminine given name commonly used in many European languages, often as a standalone name or as part of compound names.
E27948 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: Marie | Statement: [Rosemarie, hasDiminutive, Marie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marie
Context triple: [Rosemarie, hasDiminutive, Marie]
  • A. Marie
    Marie is a supporting character in the psychological thriller film "The Machinist," serving as a compassionate presence in the troubled life of the insomniac protagonist.
  • B. Marie
    Marie is the deceased beloved of the protagonist in Erich Wolfgang Korngold’s opera "Die tote Stadt," whose memory and spectral presence drive the work’s psychological drama.
  • C. Marie
    "Marie" is a 1985 biographical drama film directed by Roger Donaldson, depicting the true story of whistleblower Marie Ragghianti’s fight against political corruption in Tennessee.
  • D. Marie
    Marie is an individual known primarily as the spouse of Jess.
  • E. Marie
    Marie is a fictional character from the American sitcom "Vinnie & Bobby," which followed two construction workers navigating life and relationships in Chicago.
  • 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: Marie
Triple: [Rosemarie, hasDiminutive, Marie]
Generated description
Marie is a feminine given name commonly used in many European languages, often as a standalone name or as part of compound names.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marie
Target entity description: Marie is a feminine given name commonly used in many European languages, often as a standalone name or as part of compound names.
  • A. Marie chosen
    Marie is a widely used European given name, especially common in French-speaking countries, derived from the Hebrew name Miryam (Mary).
  • B. Marie
    Marie is an individual known primarily as the spouse of Jess.
  • C. Marie
    Marie is a small mountain village in the Alpes-Maritimes department of southeastern France, known for its picturesque setting in the Tinée Valley of the French Alps.
  • D. Marie
    Marie is the central protagonist of the romantic drama film "Passion of Mind," whose life is split between two contrasting realities that blur the line between dream and truth.
  • E. Marie
    Marie is one of the two central characters in the film "Malcolm & Marie," serving as a key figure in its intimate relationship drama.
  • F. None of above.

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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f75b2d481909fa3f603fe6bd5bd completed April 20, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_6a075f08e5b481908459a354bab00b6f completed May 15, 2026, 5:59 p.m.
NEDg Description generation batch_6a07601bb12c81909faab959182b1863 completed May 15, 2026, 6:04 p.m.
NED2 Entity disambiguation (via description) batch_6a07613541688190821fd97e069691a5 completed May 15, 2026, 6:08 p.m.
Created at: April 10, 2026, 1:42 p.m.