Triple

T1660613
Position Surface form Disambiguated ID Type / Status
Subject Helen Garner E35895 entity
Predicate givenName P17 FINISHED
Object Helen E145584 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 Garner, givenName, Helen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen
Context triple: [Helen Garner, 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 chosen
    Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
  • C. Helene
    Helene is the given name of Leni Riefenstahl, the controversial German filmmaker and actress known for her propaganda films during the Nazi era.
  • D. Penelope
    Penelope is a genus of large, arboreal guans—game birds native to Central and South American forests and belonging to the family Cracidae.
  • E. Penelope
    Penelope is the faithful and resourceful wife of Odysseus in Greek mythology, renowned for her loyalty and cleverness during his long absence in the Odyssey.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a88606aa808190aa0b421b4271f220 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90ab2a3488190a67c110a70d652c9 completed March 5, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad798680088190a24dd968aab1baf0 completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:29 p.m.