Triple

T14841565
Position Surface form Disambiguated ID Type / Status
Subject William Eythe E348976 entity
Predicate notableWork P4 FINISHED
Object Wilson
"Wilson" is a 1944 biographical drama film about U.S. President Woodrow Wilson, noted for its lavish production and multiple Academy Award wins.
E204059 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: Wilson | Statement: [William Eythe, notableWork, Wilson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilson
Context triple: [William Eythe, notableWork, Wilson]
  • A. John
    John is the given name of Colonel John Quincy, an American military officer and politician after whom John Quincy Adams was named.
  • B. John
    John B. Magruder was a Confederate major general during the American Civil War, known for his leadership in the Peninsula Campaign and his flamboyant personality.
  • C. John
    John was an abbot of Reading Abbey, a senior monastic leader in the medieval English Benedictine community.
  • D. John
    John III, Duke of Brittany, was a 14th-century French nobleman who ruled the Duchy of Brittany and played a key role in the succession disputes that led to the Breton War of Succession.
  • E. John
    John is the given first name of Jack Northrop, the pioneering American aircraft industrialist and designer.
  • 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: Wilson
Triple: [William Eythe, notableWork, Wilson]
Generated description
"Wilson" is a 1944 biographical drama film about U.S. President Woodrow Wilson, noted for its lavish production and multiple Academy Award wins.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wilson
Target entity description: "Wilson" is a 1944 biographical drama film about U.S. President Woodrow Wilson, noted for its lavish production and multiple Academy Award wins.
  • A. Wilson chosen
    "Wilson" is a 1944 American biographical film about U.S. President Woodrow Wilson, noted for its ambitious production and multiple Academy Awards.
  • B. Wilson
    Wilson is a well-known American sporting goods manufacturer recognized especially for its basketballs and other professional sports equipment.
  • C. Wilson
    Wilson is a masculine given name of English origin commonly used in English-speaking countries.
  • D. Wilson
    Wilson is a common English-language surname borne by numerous notable figures across fields such as science, politics, sports, and the arts.
  • E. Wilson
    Wilson is a city in eastern North Carolina known historically for its tobacco and textile industries and now for its cultural attractions and public gardens.
  • F. None of above.

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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28fa49c81908d1059e6cafd607f completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe38a9eb9481908ca509f484007cf6 completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe3d0eca948190b107bc593b6e5b72 completed May 8, 2026, 7:44 p.m.
NED2 Entity disambiguation (via description) batch_69fe3d94785881908911a7c6f1546d45 completed May 8, 2026, 7:46 p.m.
Created at: April 10, 2026, 1:53 a.m.