Triple

T562945
Position Surface form Disambiguated ID Type / Status
Subject Winfield Scott E13492 entity
Predicate givenName P17 FINISHED
Object Winfield
Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
 E72419 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: Winfield | Statement: [Winfield Scott, givenName, Winfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Winfield
Context triple: [Winfield Scott, givenName, Winfield]
  • A. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • B. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • C. Brewster
    Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
  • D. Brewster
    Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
  • E. Knox
    Knox is a surname most famously associated with Henry Knox, a key American Revolutionary War general and the first United States Secretary of War.
  • 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: Winfield
Triple: [Winfield Scott, givenName, Winfield]
Generated description
Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Winfield
Target entity description: Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
  • A. Lawrence
    Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
  • B. Brewster
    Brewster is a coastal town on Cape Cod in Massachusetts known for its scenic beaches, historic charm, and bayside conservation lands.
  • C. Brewster
    Brewster is the given name of Brewster Kahle, an American computer engineer and digital librarian best known as the founder of the Internet Archive.
  • D. Brewster
    Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
  • E. Knox
    Knox is a surname most famously associated with Henry Knox, a key American Revolutionary War general and the first United States Secretary of War.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49a712bc48190ba298b3c76ab11cc completed March 1, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501bdb7cc8190922432fe58cfd6cb completed March 2, 2026, 3:19 a.m.
NEDg Description generation batch_69a503b501388190baed19e781c24b4d completed March 2, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69a5077cf14081909478ea1e0fd3eff5 completed March 2, 2026, 3:43 a.m.
Created at: March 1, 2026, 7:32 p.m.