Triple

T4018766
Position Surface form Disambiguated ID Type / Status
Subject MacKenzie Scott E91227 entity
Predicate hasLastName P18 FINISHED
Object Scott
Scott is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
 E408189 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: Scott | Statement: [MacKenzie Scott, hasLastName, Scott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scott
Context triple: [MacKenzie Scott, hasLastName, Scott]
  • A. Scott
    Scott is the middle name of Francis Scott Key, the American lawyer and poet who wrote the lyrics to the United States national anthem, "The Star-Spangled Banner."
  • B. Scott
    Scott is a central fictional character in Don DeLillo’s novel "Mao II," around whom key themes of identity, terrorism, and the role of the writer in contemporary society revolve.
  • C. Kay
    Kay is a common diminutive or nickname for the given name Catherine.
  • D. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • E. Van
    Van is a historic city in eastern Anatolia, known as a major cultural and political center of ancient and medieval Armenian civilization on the shores of Lake Van.
  • 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: Scott
Triple: [MacKenzie Scott, hasLastName, Scott]
Generated description
Scott is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scott
Target entity description: Scott is a common English-language surname borne by numerous notable individuals across fields such as literature, politics, science, and entertainment.
  • A. Scott
    Scott is the middle name of Francis Scott Key, the American lawyer and poet who wrote the lyrics to the United States national anthem, "The Star-Spangled Banner."
  • B. Scott
    Scott is a central fictional character in Don DeLillo’s novel "Mao II," around whom key themes of identity, terrorism, and the role of the writer in contemporary society revolve.
  • C. Kay
    Kay is a common diminutive or nickname for the given name Catherine.
  • D. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • E. Van
    Van is a historic city in eastern Anatolia, known as a major cultural and political center of ancient and medieval Armenian civilization on the shores of Lake Van.
  • 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_69aed9618b04819081750d979d2af098 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaa984948190a252eaeb9dbae454 completed March 9, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5562bd7908190b9dfd246df8b8cc5 completed March 14, 2026, 12:35 p.m.
NEDg Description generation batch_69b556cdd05081909fea1fb0a58bc7d1 completed March 14, 2026, 12:38 p.m.
NED2 Entity disambiguation (via description) batch_69b557d445d081908f48fe3bd06f786e completed March 14, 2026, 12:43 p.m.
Created at: March 9, 2026, 3:35 p.m.