Triple

T2594106
Position Surface form Disambiguated ID Type / Status
Subject Tamika Catchings E58188 entity
Predicate familyName P18 FINISHED
Object Catchings
Catchings is the surname of Tamika Catchings, a renowned American professional basketball player and Hall of Famer.
E280901 NE FINISHED

How this triple was built (4 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: Catchings | Statement: [Tamika Catchings, familyName, Catchings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catchings
Context triple: [Tamika Catchings, familyName, Catchings]
  • A. Cunningham
    Cunningham is a common Scottish surname borne by numerous notable individuals across fields such as technology, politics, sports, and the arts.
  • B. Clemmie
    Clemmie is a diminutive given name commonly used as a nickname for Clementine.
  • C. Oates
    Oates is a surname most notably associated with American character actor Warren Oates, known for his roles in 1960s and 1970s film and television.
  • D. Darling and Pearson
    Darling and Pearson was a prominent early 20th-century Canadian architectural firm known for designing major institutional and public buildings, particularly in Toronto.
  • E. Lucinda
    Lucinda is a feminine given name used in various cultures, often considered a variant of Lucy or Lucille.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Catchings
Triple: [Tamika Catchings, familyName, Catchings]
Generated description
Catchings is the surname of Tamika Catchings, a renowned American professional basketball player and Hall of Famer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Catchings
Target entity description: Catchings is the surname of Tamika Catchings, a renowned American professional basketball player and Hall of Famer.
  • A. Cunningham
    Cunningham is a common Scottish surname borne by numerous notable individuals across fields such as technology, politics, sports, and the arts.
  • B. Clemmie
    Clemmie is a diminutive given name commonly used as a nickname for Clementine.
  • C. Oates
    Oates is a surname most notably associated with American character actor Warren Oates, known for his roles in 1960s and 1970s film and television.
  • D. Darling and Pearson
    Darling and Pearson was a prominent early 20th-century Canadian architectural firm known for designing major institutional and public buildings, particularly in Toronto.
  • E. Lucinda
    Lucinda is a feminine given name used in various cultures, often considered a variant of Lucy or Lucille.
  • F. None of above. chosen

Provenance (5 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd427f58c8190af1c1a9724158c96 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83bee4908190b5e446ddbf4e8889 completed March 10, 2026, 2:36 a.m.
NEDg Description generation batch_69af8434f61c81909bffb3f06acb733b completed March 10, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_69af84b260b881909bbd3d2825f9dea7 completed March 10, 2026, 2:40 a.m.
Created at: March 6, 2026, 9:49 p.m.