Triple

T19165976
Position Surface form Disambiguated ID Type / Status
Subject David Kajganich E469180 entity
Predicate basedOnWorkOf P15523 FINISHED
Object Dan Simmons NE NERFINISHED

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: Dan Simmons | Statement: [David Kajganich, basedOnWorkOf, Dan Simmons]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Simmons
Context triple: [David Kajganich, basedOnWorkOf, Dan Simmons]
  • A. Dan Simmons chosen
    Dan Simmons is an American author best known for his genre-spanning speculative fiction, including acclaimed works of science fiction, horror, and historical fiction.
  • B. Jerry Pournelle
    Jerry Pournelle was an American science fiction writer and essayist known for his frequent collaborations with Larry Niven on influential hard science fiction novels.
  • C. Greg Bear
    Greg Bear was an American science fiction author renowned for his hard science-based novels exploring themes such as cosmology, artificial intelligence, and the future evolution of humanity.
  • D. Jeff Long
    Jeff Long is an American author best known for his horror and thriller novels that often blend adventure, religion, and the supernatural.
  • E. Stephen Baxter
    Stephen Baxter is a British science fiction author known for his hard science narratives, expansive space operas, and collaborations with Arthur C. Clarke.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f15ee064819087f9fd822236298f completed April 20, 2026, 9:26 a.m.
Created at: April 10, 2026, 12:06 p.m.