Triple

T8016862
Position Surface form Disambiguated ID Type / Status
Subject William Moultrie E186639 entity
Predicate familyName P18 FINISHED
Object Moultrie
Moultrie is a surname most notably associated with William Moultrie, an American Revolutionary War general and political leader from South Carolina.
E707618 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: Moultrie | Statement: [William Moultrie, familyName, Moultrie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moultrie
Context triple: [William Moultrie, familyName, Moultrie]
  • A. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • B. Chattahoochee, Florida
    Chattahoochee, Florida is a small city in Gadsden County in the Florida Panhandle, known for its location near the Apalachicola River and the Florida-Georgia border.
  • C. Oakey
    Oakey is a rural town in Queensland, Australia, situated on the Darling Downs west of Toowoomba.
  • D. Taliaferro
    Taliaferro is the distinctive middle name of influential African American educator and leader Booker T. Washington.
  • E. Faison
    Faison is a surname most notably associated with American actor and comedian Donald Faison.
  • 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: Moultrie
Triple: [William Moultrie, familyName, Moultrie]
Generated description
Moultrie is a surname most notably associated with William Moultrie, an American Revolutionary War general and political leader from South Carolina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Moultrie
Target entity description: Moultrie is a surname most notably associated with William Moultrie, an American Revolutionary War general and political leader from South Carolina.
  • A. Tallassee
    Tallassee is a small city in central Alabama known for its location along the Tallapoosa River and its historic textile mill heritage.
  • B. Chattahoochee, Florida
    Chattahoochee, Florida is a small city in Gadsden County in the Florida Panhandle, known for its location near the Apalachicola River and the Florida-Georgia border.
  • C. Oakey
    Oakey is a rural town in Queensland, Australia, situated on the Darling Downs west of Toowoomba.
  • D. Taliaferro
    Taliaferro is the distinctive middle name of influential African American educator and leader Booker T. Washington.
  • E. Faison
    Faison is a surname most notably associated with American actor and comedian Donald Faison.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3df4f1b8819089a8b67f136bce9a completed March 31, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56ba88b88190ad279d79d7f0ffd7 completed March 31, 2026, 11:20 p.m.
NEDg Description generation batch_69cc58a9e94081908980e2c60be38642 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cbaefb481909eb325f0d27675c0 completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:20 p.m.