Triple

T9111108
Position Surface form Disambiguated ID Type / Status
Subject H. T. Lowe-Porter E218601 entity
Predicate givenName P17 FINISHED
Object Helen
Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
 E779044 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: [H. T. Lowe-Porter, givenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Helen
Context triple: [H. T. Lowe-Porter, 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 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.
  • C. Helen
    Helen is the given first name of Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
  • D. 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.
  • E. Helen
    Helen is a character from the British television sitcom "Out of This World."
  • 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: [H. T. Lowe-Porter, givenName, Helen]
Generated description
Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Helen
Target entity description: Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
  • 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 the given first name of Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
  • 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 name of Maria Helen Van Schaack, likely used as her primary personal name.
  • E. Helen
    Helen is the given first name of New Zealand actress Pat Evison, known for her work in film, television, and theatre.
  • F. None of above. chosen

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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca847102881908f9d86ce9883fb1a completed April 1, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030467b188190a6d99bf2fc65207d completed April 3, 2026, 9:25 p.m.
NEDg Description generation batch_69d0316f47c88190920843b469d15069 completed April 3, 2026, 9:30 p.m.
NED2 Entity disambiguation (via description) batch_69d032778adc8190a087497507a6e1ca completed April 3, 2026, 9:34 p.m.
Created at: March 30, 2026, 7:16 p.m.