Triple

T8317838
Position Surface form Disambiguated ID Type / Status
Subject Eclogues E194749 entity
Predicate influenced P9 FINISHED
Object Edmund Spenser E98292 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: Edmund Spenser | Statement: [Eclogues, influenced, Edmund Spenser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edmund Spenser
Context triple: [Eclogues, influenced, Edmund Spenser]
  • A. Edmund Spenser chosen
    Edmund Spenser was a major English Renaissance poet best known for his epic allegorical poem "The Faerie Queene."
  • B. Arthur Brooke
    Arthur Brooke was a 16th-century English poet best known for writing the narrative poem that served as the primary source for Shakespeare’s "Romeo and Juliet."
  • C. Philip Wyatt
    Philip Wyatt was a 19th-century British architect from the prominent Wyatt architectural family, known for his work on notable country houses and neoclassical designs.
  • D. Thomas Wyatt
    Thomas Wyatt was a 16th-century English poet and diplomat credited with introducing the sonnet form into English literature during the Renaissance.
  • E. Sir Philip Sidney
    Sir Philip Sidney was a 16th-century English poet, courtier, and soldier renowned for works like "Astrophel and Stella" and "The Defence of Poesy."
  • 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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f630ea881909fb639383e60aee9 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd9596891c81909296050d0a8117ca completed April 1, 2026, 10 p.m.
Created at: March 30, 2026, 5:55 p.m.