Triple

T15893708
Position Surface form Disambiguated ID Type / Status
Subject Helen Shaver E385395 entity
Predicate givenName P17 FINISHED
Object Helen
Helen is a feminine given name of Greek origin, historically associated with figures such as Helen of Troy and widely used in English-speaking countries.
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 Shaver, givenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Helen Shaver, givenName, Helen]
  • A. Helen
    Helen is the birth name of Beatrix Potter, the renowned English writer and illustrator best known for her children's books featuring animal characters such as Peter Rabbit.
  • B. 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.
  • C. Helen
    Helen is the birth name of P. L. Travers, the Australian-British author best known for creating the "Mary Poppins" series.
  • D. Helen
    Helen is the given first name of New Zealand actress Pat Evison, known for her work in film, television, and theatre.
  • 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 Shaver, givenName, Helen]
Generated description
Helen is a feminine given name of Greek origin, historically associated with figures such as Helen of Troy and widely used in English-speaking countries.
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 figures such as Helen of Troy and widely used in English-speaking countries.
  • 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 name of Lady Helen Taylor, a British aristocrat and member of the extended royal family known for her work in the arts and fashion.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563727cc819086b5c18b655dd7f6 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0497cb481908e8ea4ebb9c4039d completed May 9, 2026, 10:08 p.m.
NEDg Description generation batch_69ffb1b0ac6481908d2e6106c0984d21 completed May 9, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_69ffb2461ea48190ba05f7da71b0f80f completed May 9, 2026, 10:16 p.m.
Created at: April 10, 2026, 4:51 a.m.