Triple

T929073
Position Surface form Disambiguated ID Type / Status
Subject William Harvey E20050 entity
Predicate name P16 FINISHED
Object William Harvey E20050 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: William Harvey | Statement: [William Harvey, name, William Harvey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Harvey
Context triple: [William Harvey, name, William Harvey]
  • A. William Harvey chosen
    William Harvey was a 17th-century English physician best known for discovering and describing the circulation of blood in the human body.
  • B. Johannes Müller
    Johannes Müller was a pioneering 19th-century German physiologist whose work helped establish modern experimental physiology and deeply influenced a generation of scientists.
  • C. William Price
    William Price was an 18th-century architect and builder active in colonial Boston, known for his work on prominent structures such as the Old North Church.
  • D. Ibn al-Nafis
    Ibn al-Nafis was a 13th-century Syrian physician and polymath best known for his pioneering description of the pulmonary circulation of the blood.
  • E. Herman Boerhaave
    Herman Boerhaave was a pioneering Dutch physician, botanist, and chemist often regarded as the father of clinical teaching and modern academic hospital medicine.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b34775ac8190aabbd047a36cec6b completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee0f01ac8190b280829dbc5ef102 completed March 4, 2026, 8:32 a.m.
Created at: March 1, 2026, 7:40 p.m.