Triple

T6716561
Position Surface form Disambiguated ID Type / Status
Subject Daniel Bliss E153283 entity
Predicate name P16 FINISHED
Object Daniel Bliss E153283 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: Daniel Bliss | Statement: [Daniel Bliss, name, Daniel Bliss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Bliss
Context triple: [Daniel Bliss, name, Daniel Bliss]
  • A. Daniel Bliss chosen
    Daniel Bliss was a 19th-century American missionary and educator best known as the founding president of the American University of Beirut in Lebanon.
  • B. Daniel Pratt
    Daniel Pratt was a 19th-century American industrialist and cotton gin manufacturer who became one of Alabama’s leading entrepreneurs and the founder of the town of Prattville.
  • C. Timothy Church
    Timothy Church is a notable individual who bears the surname Church, recognized for his contributions in his respective field.
  • D. John Davenport
    John Davenport was a prominent 17th-century English Puritan clergyman and co-founder of the New Haven Colony in New England.
  • E. Charles Reed Bishop
    Charles Reed Bishop was a 19th-century American businessman and philanthropist in Hawaii, best known for his influential role in the Hawaiian Kingdom and for establishing major educational and cultural institutions there.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d125db3c8190aad28919226a16da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700993128819081614ccfa68d7320 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:07 p.m.