Triple

T20931432
Position Surface form Disambiguated ID Type / Status
Subject White Div E515479 entity
Predicate opponent P437 FINISHED
Object Kay Kavus E120198 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: Kay Kavus | Statement: [White Div, opponent, Kay Kavus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kay Kavus
Context triple: [White Div, opponent, Kay Kavus]
  • A. Kay Kavus chosen
    Kay Kavus is a legendary king of Iran in Ferdowsi’s epic Shahnameh, known for his hubris, ill-fated ambitions, and reliance on heroes like Rostam to rescue him from his own reckless schemes.
  • B. Tavo Kaynin
    Tavo Kaynin is a character from Terry Brooks's Shannara universe who appears in the novel "The Black Elfstone."
  • C. Nick Bakay
    Nick Bakay is an American actor, writer, and comedian best known as the voice of the sarcastic cat Salem Saberhagen on the television series "Sabrina the Teenage Witch."
  • D. Jeff Kaake
    Jeff Kaake is an American actor best known for his leading role as Captain John Boon in the science fiction television series "Space Rangers."
  • E. Mark Korven
    Mark Korven is a Canadian film and television composer best known for his unsettling, atmospheric scores for horror projects such as The Witch and The Lighthouse.
  • 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_69e0b4fb431c8190b9d40e6a72f0cc87 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f65681b4819083c7ef6b44ba4bdb completed April 21, 2026, 4 a.m.
NED1 Entity disambiguation (via context triple) batch_6a095055baa08190b45755e9ce4102c3 completed May 17, 2026, 5:21 a.m.
Created at: April 16, 2026, 12:49 p.m.