Triple

T19228249
Position Surface form Disambiguated ID Type / Status
Subject Menelaion E480796 entity
Predicate secondaryDeityOrHero P23286 FINISHED
Object Helen NE NERFINISHED

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: Helen | Statement: [Menelaion, secondaryDeityOrHero, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Menelaion, secondaryDeityOrHero, Helen]
  • A. Helen
    Helen is a central character in Ernest Hemingway’s short story “The Snows of Kilimanjaro,” portrayed as the wealthy, devoted wife and companion of the writer Harry during his final, reflective days in Africa.
  • B. Helen
    Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
  • C. Helen
    Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
  • D. Helen
    Helen is the birth name of British television presenter Tess Daly, best known for co-hosting the BBC dance competition show "Strictly Come Dancing."
  • E. Helen
    Helen is a Greek and Danish princess of the early 20th century, known as Princess Helen of Greece and Denmark.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is a famed figure of Greek mythology, renowned as the most beautiful woman in the world and whose abduction by Paris sparked the Trojan War.
  • A. Helen chosen
    Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
  • B. Helen
    Helen is a feminine given name of Greek origin, traditionally associated with beauty and light and popular in many English-speaking countries.
  • C. Helen
    Helen is a tragedy by Euripides that reimagines the myth of Helen of Troy by portraying her as an innocent woman whose phantom was taken to Troy while she remained in Egypt.
  • D. Helen
    Helen is a Greek and Danish princess of the early 20th century, known as Princess Helen of Greece and Denmark.
  • E. Helen
    Helen is a fictional protagonist associated with a narrative set in or around New York City's Central Park.
  • F. None of above.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryDeityOrHero
Context triple: [Menelaion, secondaryDeityOrHero, Helen]
  • A. guardianDeitiesOrFigures
    Indicates a protective or watchful relationship in which certain deities or figures serve as guardians over specific people, places, objects, or domains.
  • B. otherDeity
    Indicates that one deity is distinct from and not identical to another deity within a given context or system.
  • C. roleOfReferencedDeity
    Indicates that one entity specifies the function, status, or position held by a deity that is referenced in relation to another entity or context.
  • D. mythologicalRole
    Indicates the specific function, duty, or status an entity holds within a mythological or legendary context.
  • E. worshippedAlongside chosen
    Indicates that two deities or sacred figures were venerated together within the same religious context, ritual, or cult practice.
  • F. None of above.

Provenance (3 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_69d8e8ccb8f48190ad420098e74fb1db completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa9b167881908fc46d46c2d53423 completed April 20, 2026, 10:06 a.m.
PD Predicate disambiguation batch_69e4dcfae6f081909cc173cf71a5005c completed April 19, 2026, 1:47 p.m.
Created at: April 10, 2026, 1:25 p.m.