Triple

T2247565
Position Surface form Disambiguated ID Type / Status
Subject Dora Sigerson Shorter E49540 entity
Predicate hasGivenName P17 FINISHED
Object Dora E49540 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: Dora | Statement: [Dora Sigerson Shorter, hasGivenName, Dora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dora
Context triple: [Dora Sigerson Shorter, hasGivenName, Dora]
  • A. Dora chosen
    Dora is the given name of Dora Sigerson Shorter, an Irish poet associated with the late 19th- and early 20th-century literary revival.
  • B. Dora Riparia
    Dora Riparia is a river in northwestern Italy that flows through the city of Turin before joining the Po River.
  • C. Lucy
    "Lucy" is a 2014 science fiction action film directed by Luc Besson, in which Scarlett Johansson plays a woman who gains extraordinary mental and physical abilities after a drug enters her system.
  • D. Lucy
    Lucy Hawking is a British journalist, novelist, and educator best known for her children’s science books co-written with her father, physicist Stephen Hawking.
  • E. Lucy
    Lucy is the given name of Lucy Flucker Knox, the wife of American Revolutionary War General Henry Knox and a notable figure in early American history.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0ed5c38819080b45ea398fb59f2 completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f0361d08190922d21c89d32c869 completed March 9, 2026, 8:04 a.m.
Created at: March 4, 2026, 7:47 p.m.