Triple

T7007767
Position Surface form Disambiguated ID Type / Status
Subject Henry Daniell E162500 entity
Predicate name P16 FINISHED
Object Henry Daniell E162500 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: Henry Daniell | Statement: [Henry Daniell, name, Henry Daniell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry Daniell
Context triple: [Henry Daniell, name, Henry Daniell]
  • A. Henry Daniell chosen
    Henry Daniell was a British character actor renowned for his many villainous and aristocratic roles in classic Hollywood films of the 1930s and 1940s.
  • B. George Davison
    George Davison is an Anglican bishop who serves as a senior cleric in the Church of Ireland.
  • C. Edward Walson
    Edward Walson is a film producer known for working on projects such as Woody Allen’s romantic comedy "Magic in the Moonlight."
  • D. Henry Samson
    Henry Samson was a young passenger on the Mayflower who later became a settler in Plymouth Colony in early 17th-century New England.
  • E. Henry Martyn
    Henry Martyn was an early 19th-century Anglican missionary and Bible translator known for his pioneering evangelistic work in India and Persia.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc36e3fc8190957445132a9ffb5f completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a43c3a081909b9150d36ba107f5 completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:33 p.m.