Triple

T17583065
Position Surface form Disambiguated ID Type / Status
Subject Briana Scurry E428251 entity
Predicate familyName P18 FINISHED
Object Scurry
Scurry is the surname of Briana Scurry, a renowned American soccer goalkeeper and two-time Olympic gold medalist.
 E1276425 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: Scurry | Statement: [Briana Scurry, familyName, Scurry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scurry
Context triple: [Briana Scurry, familyName, Scurry]
  • A. Burlada
    Burlada is a municipality in northern Spain, located in the autonomous community of Navarre and forming part of the metropolitan area of Pamplona.
  • B. Chickasha
    Chickasha is a small city in Grady County, Oklahoma, known historically as a regional agricultural and railroad hub and now home to the University of Science and Arts of Oklahoma.
  • C. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • D. Hinson
    Hinson is a surname most notably associated with former professional basketball player Roy Hinson.
  • E. Binger
    Binger is the term used to refer to inhabitants of the German town of Bingen am Rhein.
  • 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: Scurry
Triple: [Briana Scurry, familyName, Scurry]
Generated description
Scurry is the surname of Briana Scurry, a renowned American soccer goalkeeper and two-time Olympic gold medalist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scurry
Target entity description: Scurry is the surname of Briana Scurry, a renowned American soccer goalkeeper and two-time Olympic gold medalist.
  • A. Burlada
    Burlada is a municipality in northern Spain, located in the autonomous community of Navarre and forming part of the metropolitan area of Pamplona.
  • B. Chickasha
    Chickasha is a small city in Grady County, Oklahoma, known historically as a regional agricultural and railroad hub and now home to the University of Science and Arts of Oklahoma.
  • C. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • D. Hinson
    Hinson is a surname most notably associated with former professional basketball player Roy Hinson.
  • E. Binger
    Binger is the term used to refer to inhabitants of the German town of Bingen am Rhein.
  • 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e463cf556881908d2935b3761f65df completed April 19, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01ddef82d48190a5940f7da646c380 completed May 11, 2026, 1:47 p.m.
NEDg Description generation batch_6a01de93c1448190aa2328919d407252 completed May 11, 2026, 1:50 p.m.
NED2 Entity disambiguation (via description) batch_6a01e05515d88190b343ebc1aad4a351 completed May 11, 2026, 1:57 p.m.
Created at: April 10, 2026, 5:50 a.m.