Triple

T8407110
Position Surface form Disambiguated ID Type / Status
Subject Sebastián Abreu E198527 entity
Predicate givenName P17 FINISHED
Object Washington
Washington is the given first name of Uruguayan former professional footballer and coach Sebastián "Loco" Abreu.
 E746604 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: Washington | Statement: [Sebastián Abreu, givenName, Washington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Washington
Context triple: [Sebastián Abreu, givenName, Washington]
  • A. Washington
    Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
  • B. Washington
    Washington is a common English surname most famously borne by George Washington, the first president of the United States.
  • C. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • D. Washington
    Washington is a small rural town in Berkshire County in western Massachusetts, known for its forested landscape and quiet, sparsely populated character.
  • E. Washington
    Washington is a rapid transit station on Chicago's 'L' system, formerly serving the CTA Blue Line in the downtown Loop.
  • 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: Washington
Triple: [Sebastián Abreu, givenName, Washington]
Generated description
Washington is the given first name of Uruguayan former professional footballer and coach Sebastián "Loco" Abreu.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Washington
Target entity description: Washington is the given first name of Uruguayan former professional footballer and coach Sebastián "Loco" Abreu.
  • A. Washington
    Washington is a common English surname most famously borne by George Washington, the first president of the United States.
  • B. Washington
    Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
  • C. Washington
    Washington is a rapid transit station on Chicago's 'L' system, formerly serving the CTA Blue Line in the downtown Loop.
  • D. Washington
    Washington is a town in the City of Sunderland in Tyne and Wear, England, historically part of County Durham and often noted for its links to the family of George Washington.
  • E. Washington
    Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb831409308190981089c303ebaef4 completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69cebb37161081908452cc449b4e903e completed April 2, 2026, 6:53 p.m.
NEDg Description generation batch_69cebda8e7f4819083b6885f874554f1 completed April 2, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69cebe5df4888190bf741e332af3e21e completed April 2, 2026, 7:07 p.m.
Created at: March 30, 2026, 6:05 p.m.