Triple

T5059496
Position Surface form Disambiguated ID Type / Status
Subject Theodore Dwight Woolsey E113987 entity
Predicate familyName P18 FINISHED
Object Woolsey
Woolsey is a surname most notably associated with Theodore Dwight Woolsey, a prominent 19th-century American academic and president of Yale College.
 E491265 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: Woolsey | Statement: [Theodore Dwight Woolsey, familyName, Woolsey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Woolsey
Context triple: [Theodore Dwight Woolsey, familyName, Woolsey]
  • A. Buckley
    Buckley is a small city in Washington State known for its rural character and proximity to Mount Rainier.
  • B. Buckley
    Buckley is a surname most prominently associated with William F. Buckley Jr., the influential American conservative author and founder of National Review.
  • C. Willard
    Willard is a masculine given name of Old English origin meaning "resolute" or "strong-willed."
  • D. Shaughnessy
    Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
  • E. Nunes
    Nunes is a common Portuguese surname borne by numerous individuals, including athletes, politicians, and public figures in Portuguese-speaking countries.
  • 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: Woolsey
Triple: [Theodore Dwight Woolsey, familyName, Woolsey]
Generated description
Woolsey is a surname most notably associated with Theodore Dwight Woolsey, a prominent 19th-century American academic and president of Yale College.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Woolsey
Target entity description: Woolsey is a surname most notably associated with Theodore Dwight Woolsey, a prominent 19th-century American academic and president of Yale College.
  • A. Buckley
    Buckley is a small city in Washington State known for its rural character and proximity to Mount Rainier.
  • B. Buckley
    Buckley is a surname most prominently associated with William F. Buckley Jr., the influential American conservative author and founder of National Review.
  • C. Willard
    Willard is a masculine given name of Old English origin meaning "resolute" or "strong-willed."
  • D. Shaughnessy
    Shaughnessy is an affluent residential neighbourhood in Vancouver, British Columbia, known for its large heritage homes and tree-lined streets.
  • E. Nunes
    Nunes is a common Portuguese surname borne by numerous individuals, including athletes, politicians, and public figures in Portuguese-speaking countries.
  • 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_69bd443c0c8c81908663b77afb28e165 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7453daac8190b2946702c6c4bd93 completed March 20, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea49283f48190b5db5ad78f332f95 completed March 21, 2026, 2 p.m.
NEDg Description generation batch_69bea67c2c3c8190af0caba391bfe69c completed March 21, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69beaa2c9bf88190b9f96474a1b4f13d completed March 21, 2026, 2:24 p.m.
Created at: March 20, 2026, 1:38 p.m.