Triple

T15099375
Position Surface form Disambiguated ID Type / Status
Subject Lola (Damn Yankees) E360621 entity
Predicate triesToSeduce P91606 FINISHED
Object Joe Boyd E894973 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: Joe Boyd | Statement: [Lola (Damn Yankees), triesToSeduce, Joe Boyd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joe Boyd
Context triple: [Lola (Damn Yankees), triesToSeduce, Joe Boyd]
  • A. Joe Boyd chosen
    Joe Boyd is the middle-aged baseball fan in the musical "Damn Yankees" who sells his soul to the Devil to help his beloved Washington Senators defeat the New York Yankees.
  • B. Walter Boyd
    Walter Boyd is a former Jamaican international footballer best known for his prolific goal-scoring and charismatic playing style as a forward in the 1990s and early 2000s.
  • C. Ernest Young
    Ernest Young is a prominent American constitutional law scholar and professor at Duke University School of Law.
  • D. Fred Searing
    Fred Searing is the central protagonist of the comedy film "Hall Pass," around whom the story’s marital and midlife-crisis hijinks revolve.
  • E. Ted Ross
    Ted Ross was an American actor best known for his Tony- and Oscar-winning portrayal of the Cowardly Lion in the stage and film versions of "The Wiz."
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054f00388190a5123d9f4a869b96 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae230d148190a343ac92fb089902 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:04 a.m.