Triple

T8388015
Position Surface form Disambiguated ID Type / Status
Subject The Dark Tower III: The Waste Lands E197868 entity
Predicate publisher P29 FINISHED
Object Grant E192779 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: Grant | Statement: [The Dark Tower III: The Waste Lands, publisher, Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant
Context triple: [The Dark Tower III: The Waste Lands, publisher, Grant]
  • A. Grant
    Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
  • B. Grant chosen
    Grant is a publishing company best known for releasing special and limited editions of Stephen King’s works, including volumes in The Dark Tower series.
  • C. Jones
    Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
  • D. Red Grant
    Red Grant is a ruthless, psychopathic assassin and primary antagonist in the James Bond franchise, most prominently appearing as SPECTRE’s top killer in the film and novel "From Russia, with Love."
  • E. Guber
    Guber is a surname most prominently associated with American film producer and executive Peter Guber.
  • 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_69ca82f749388190bffbea6dfb509016 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb81090f688190a3a8d1680383c361 completed March 31, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d1ffa988190a7b0a6b1017e144d completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:03 p.m.