Triple

T6417009
Position Surface form Disambiguated ID Type / Status
Subject James G. Blaine E127853 entity
Predicate familyName P18 FINISHED
Object Blaine
Blaine is a surname most notably associated with James G. Blaine, a prominent 19th-century American statesman and politician.
 E591737 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: Blaine | Statement: [James G. Blaine, familyName, Blaine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blaine
Context triple: [James G. Blaine, familyName, Blaine]
  • A. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • B. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • C. Addison
    Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
  • D. Addison
    Addison is the middle name of Lewis Armistead, a Confederate general best known for his role in Pickett’s Charge during the American Civil War.
  • E. Addison
    Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
  • 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: Blaine
Triple: [James G. Blaine, familyName, Blaine]
Generated description
Blaine is a surname most notably associated with James G. Blaine, a prominent 19th-century American statesman and politician.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blaine
Target entity description: Blaine is a surname most notably associated with James G. Blaine, a prominent 19th-century American statesman and politician.
  • A. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • B. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • C. Addison
    Addison is a Chicago Transit Authority 'L' station on the Blue Line serving the city's Northwest Side.
  • D. Addison
    Addison is the middle name of Lewis Armistead, a Confederate general best known for his role in Pickett’s Charge during the American Civil War.
  • E. Addison
    Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068ea06b08190901e0c0a18fd5170 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640ce3f9481908fa96fb5b2bc8db9 completed March 27, 2026, 8:33 a.m.
NEDg Description generation batch_69c6415095488190ae506fb8ec95d4c6 completed March 27, 2026, 8:35 a.m.
NED2 Entity disambiguation (via description) batch_69c641b5ac988190bde502b6637736fe completed March 27, 2026, 8:37 a.m.
Created at: March 22, 2026, 4:42 p.m.