Triple

T482364
Position Surface form Disambiguated ID Type / Status
Subject William Erasmus Darwin E9197 entity
Predicate mother P120 FINISHED
Object Emma Darwin E7447 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: Emma Darwin | Statement: [William Erasmus Darwin, mother, Emma Darwin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Darwin
Context triple: [William Erasmus Darwin, mother, Emma Darwin]
  • A. Emma Darwin chosen
    Emma Darwin was an English woman best known as the devoted wife and first cousin of naturalist Charles Darwin, who supported his scientific work and managed their large family.
  • B. Marianne Darwin
    Marianne Darwin was a member of the Darwin family and one of the siblings in the generation that included naturalist Charles Darwin.
  • C. Mary Eleanor Darwin
    Mary Eleanor Darwin was one of the daughters of naturalist Charles Darwin and his wife Emma, who died in early childhood.
  • D. Sarah Darwin
    Sarah Darwin is a British evolutionary biologist and science communicator, and a descendant of naturalist Charles Darwin.
  • E. Anne Elizabeth Darwin
    Anne Elizabeth Darwin was the beloved eldest daughter of naturalist Charles Darwin, whose early death deeply affected him and influenced his views on religion and suffering.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f05a7f6c819082b4a5a3e69468a6 completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b23a3ddc8190a685a63923d1d175 completed March 1, 2026, 9:40 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.