Triple

T19678167
Position Surface form Disambiguated ID Type / Status
Subject Alexander E472509 entity
Predicate loverOf P7325 FINISHED
Object Helen
Helen is a figure from Greek mythology, famed for her extraordinary beauty and central role in sparking the Trojan War.
E145584 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: Helen | Statement: [Alexander, loverOf, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Alexander, loverOf, Helen]
  • A. Helen
    Helen is a central survivor and maternal figure in the post-apocalyptic film "Waterworld," known for her determination to protect the child Enola and seek the mythical Dryland.
  • B. Helen
    Helen is the birth name of P. L. Travers, the Australian-British author best known for creating the "Mary Poppins" series.
  • C. Helen
    Helen is a fictional protagonist associated with a narrative set in or around New York City's Central Park.
  • D. 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.
  • E. Helen
    Helen is a person characterized in this context by her adversarial relationship with Deacon.
  • 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: Helen
Triple: [Alexander, loverOf, Helen]
Generated description
Helen is a figure from Greek mythology, famed for her extraordinary beauty and central role in sparking the Trojan War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is a figure from Greek mythology, famed for her extraordinary beauty and central role in sparking 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.

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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bda8348190b0c7816c50aca923 completed April 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ab8c90b4819085da8965e0d269eb completed May 15, 2026, 11:26 p.m.
NEDg Description generation batch_6a07ae6ebfc0819095ff74ed188e4031 completed May 15, 2026, 11:38 p.m.
NED2 Entity disambiguation (via description) batch_6a07aee534188190ba164f9ddb656620 completed May 15, 2026, 11:40 p.m.
Created at: April 10, 2026, 1:45 p.m.