Triple

T12331438
Position Surface form Disambiguated ID Type / Status
Subject Helen Dortch Longstreet E293969 entity
Predicate givenName P17 FINISHED
Object Helen
Helen is a feminine given name of Greek origin, historically associated with beauty and light and borne by numerous notable figures across literature, mythology, and real life.
E791531 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: [Helen Dortch Longstreet, givenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Helen Dortch Longstreet, givenName, 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 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.
  • D. Helen
    Helen is a fictional character from the 1930 aviation war film "Hell's Angels," which is renowned for its groundbreaking aerial combat sequences and early sound-era spectacle.
  • 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: [Helen Dortch Longstreet, givenName, Helen]
Generated description
Helen is a feminine given name of Greek origin, historically associated with beauty and light and borne by numerous notable figures across literature, mythology, and real life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Helen
Target entity description: Helen is a feminine given name of Greek origin, historically associated with beauty and light and borne by numerous notable figures across literature, mythology, and real life.
  • A. Helen chosen
    Helen is a feminine given name of Greek origin, traditionally associated with beauty and light and popular in many English-speaking countries.
  • B. Helen
    Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
  • C. Helen
    Helen is the given name of Maria Helen Van Schaack, likely used as her primary personal name.
  • D. Helen
    Helen is the given first name of the British philosopher and life peer Mary Warnock.
  • E. Helen
    Helen is the given first name of Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f634ee08190b4f533505d402219 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e9114f48190988b84eaec2e810f completed May 2, 2026, 3:56 p.m.
NEDg Description generation batch_69f61fd2429c8190a8a7c46c312e262d completed May 2, 2026, 4:01 p.m.
NED2 Entity disambiguation (via description) batch_69f623f5aa608190bce3e62e08077216 completed May 2, 2026, 4:19 p.m.
Created at: April 8, 2026, 9:53 p.m.