Triple

T16024476
Position Surface form Disambiguated ID Type / Status
Subject Helen Adam E388682 entity
Predicate hasGivenName P17 FINISHED
Object Helen unclear NED1 NE FINISHED

How this triple was built (2 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 Adam, hasGivenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Helen Adam, hasGivenName, Helen]
  • A. 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.
  • B. Helen
    Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
  • C. Helen
    Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
  • D. Helen
    Helen is the birth name of British television presenter Tess Daly, best known for co-hosting the BBC dance competition show "Strictly Come Dancing."
  • E. Helen
    Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (3 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183258c708190acf1588c7ccb254c completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:55 a.m.