Triple

T3639841
Position Surface form Disambiguated ID Type / Status
Subject Willie Stargell E77158 entity
Predicate notableTeammate P2649 FINISHED
Object Kent Tekulve E161942 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: Kent Tekulve | Statement: [Willie Stargell, notableTeammate, Kent Tekulve]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kent Tekulve
Context triple: [Willie Stargell, notableTeammate, Kent Tekulve]
  • A. Kent Tekulve chosen
    Kent Tekulve is a former Major League Baseball relief pitcher best known for his submarine delivery and key role in the Pittsburgh Pirates’ 1979 World Series championship.
  • B. Gregory Nussbaum
    Gregory Nussbaum is a film editor known for his work on the 2008 comic-book adaptation "The Spirit."
  • C. Will Knaak
    Will Knaak is an American guitarist and songwriter best known as a member of the alternative rock band Blue October.
  • D. David S. Kaufman
    David S. Kaufman was a 19th-century Texas politician and statesman who served as a U.S. Congressman and played a significant role in the early political development of Texas.
  • E. Stephen M. Kellen
    Stephen M. Kellen was a prominent financier and philanthropist known for his leadership at Arnhold and S. Bleichroeder and his significant support of cultural and educational institutions.
  • 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc32b83188190bfc0ed4dc8f66730 completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f2a8a5c8190b84dcf4b4b8a939e completed March 13, 2026, 5:53 p.m.
Created at: March 8, 2026, 3:24 p.m.