Triple

T17660224
Position Surface form Disambiguated ID Type / Status
Subject Malcolmina E440229 entity
Predicate hasComponent P35 FINISHED
Object Malcolm
Malcolm is a given name commonly used in English-speaking countries, historically of Scottish origin and borne by various notable figures in politics, arts, and popular culture.
E95676 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: Malcolm | Statement: [Malcolmina, hasComponent, Malcolm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malcolm
Context triple: [Malcolmina, hasComponent, Malcolm]
  • A. John
    John "Muk Muk" Burke is an individual known by the nickname "Muk Muk," suggesting a distinctive personal or public persona associated with that moniker.
  • B. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • C. John
    John Brabourne was a British film and television producer and peer, known for producing works such as the 1979 adaptation of "Murder on the Orient Express."
  • D. John
    John is the given name of Sir John Lennard-Jones, a pioneering British theoretical chemist known for his work on intermolecular forces and the Lennard-Jones potential.
  • E. John
    John II, Duke of Bourbon was a 15th-century French nobleman and military leader who played a significant role in the Hundred Years' War.
  • 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: Malcolm
Triple: [Malcolmina, hasComponent, Malcolm]
Generated description
Malcolm is a given name commonly used in English-speaking countries, historically of Scottish origin and borne by various notable figures in politics, arts, and popular culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Malcolm
Target entity description: Malcolm is a given name commonly used in English-speaking countries, historically of Scottish origin and borne by various notable figures in politics, arts, and popular culture.
  • A. Malcolm chosen
    Malcolm is a masculine given name of Scottish origin, traditionally meaning "disciple of Saint Columba."
  • B. Malcolm
    Malcolm is the highly intelligent, often sarcastic middle child and main protagonist of the sitcom "Malcolm in the Middle."
  • C. Malcolm
    Malcolm is a central human character in "Dawn of the Planet of the Apes," portrayed as a compassionate leader who strives to build peace and cooperation between humans and the intelligent apes.
  • D. Malcolm
    Malcolm is the central child protagonist of the 2016 horror film "The Boy," around whom the movie’s eerie and suspenseful events revolve.
  • E. Malcolm
    Malcolm is a central fictional character, likely portrayed as a complex protagonist whose experiences and choices drive the narrative of the story "Burn."
  • 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46ea5270c81909d374c9e3946cea6 completed April 19, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02f824d1188190a56342faea873f30 completed May 12, 2026, 9:51 a.m.
NEDg Description generation batch_6a02f94b4748819096a529f04525cf03 completed May 12, 2026, 9:56 a.m.
NED2 Entity disambiguation (via description) batch_6a02fa28ac0881909d9d4273ea576273 completed May 12, 2026, 10 a.m.
Created at: April 10, 2026, 9:42 a.m.