Triple

T3134509
Position Surface form Disambiguated ID Type / Status
Subject Lynn Swann E65495 entity
Predicate familyName P18 FINISHED
Object Swann
Swann is a surname most prominently associated with Lynn Swann, a Hall of Fame American football wide receiver and former politician.
 E330624 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: Swann | Statement: [Lynn Swann, familyName, Swann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Swann
Context triple: [Lynn Swann, familyName, Swann]
  • A. Maurice
    Maurice is a 1987 British romantic drama film, based on E.M. Forster’s novel, that explores same-sex love and class in early 20th-century England.
  • B. Maurice
    Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
  • C. Marcel
    Marcel is a masculine given name of French origin, commonly used in various European countries.
  • D. Monsieur Bonacieux
    Monsieur Bonacieux is a minor but pivotal character in Alexandre Dumas' novel "The Three Musketeers," known as Constance Bonacieux's older, miserly husband and d'Artagnan's landlord in Paris.
  • E. Bernard
    Bernard is a masculine given name of Old French and Germanic origin, historically borne by notable figures such as military leaders and saints.
  • 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: Swann
Triple: [Lynn Swann, familyName, Swann]
Generated description
Swann is a surname most prominently associated with Lynn Swann, a Hall of Fame American football wide receiver and former politician.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Swann
Target entity description: Swann is a surname most prominently associated with Lynn Swann, a Hall of Fame American football wide receiver and former politician.
  • A. Maurice
    Maurice is a 1987 British romantic drama film, based on E.M. Forster’s novel, that explores same-sex love and class in early 20th-century England.
  • B. Maurice
    Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
  • C. Marcel
    Marcel is a masculine given name of French origin, commonly used in various European countries.
  • D. Monsieur Bonacieux
    Monsieur Bonacieux is a minor but pivotal character in Alexandre Dumas' novel "The Three Musketeers," known as Constance Bonacieux's older, miserly husband and d'Artagnan's landlord in Paris.
  • E. Bernard
    Bernard is a masculine given name of Old French and Germanic origin, historically borne by notable figures such as military leaders and saints.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada562540081908627950dd0b56a1e completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f84d8288190b1f48fa0f5c10773 completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2102e35b08190ad9ca397f0c937da completed March 12, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b21458b07081909d75886e0d9f88e9 completed March 12, 2026, 1:18 a.m.
Created at: March 8, 2026, 3:05 p.m.