Triple

T9450605
Position Surface form Disambiguated ID Type / Status
Subject Helen Mack E227878 entity
Predicate givenName P17 FINISHED
Object Helen
Helen is a feminine given name of Greek origin, traditionally associated with beauty and light and popular in many 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 Mack, givenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Helen Mack, givenName, Helen]
  • A. Helen
    Helen is the birth name of P. L. Travers, the Australian-British author best known for creating the "Mary Poppins" series.
  • B. Helen
    Helen is the given first name of Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
  • C. 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.
  • D. Helen
    Helen is the central character in the novel "The Spare Room," around whom the story’s emotional and narrative developments revolve.
  • E. Helen
    Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
  • 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 Mack, givenName, Helen]
Generated description
Helen is a feminine given name of Greek origin, traditionally associated with beauty and light and popular in many 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, traditionally associated with beauty and light and popular in many 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 Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
  • E. 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.
  • 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_69ca8439f8bc8190997f2ef40c9f0bc2 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f6649a48190b6844daa6202efe5 completed April 1, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12268429c8190bf2fd0f3ea4dac4a completed April 4, 2026, 2:38 p.m.
NEDg Description generation batch_69d1235eccb88190943355bdc4e3a873 completed April 4, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69d123e548e88190a85c8b3822879b72 completed April 4, 2026, 2:44 p.m.
Created at: March 30, 2026, 7:51 p.m.