Triple

T885339
Position Surface form Disambiguated ID Type / Status
Subject Earl Monroe E19117 entity
Predicate familyName P18 FINISHED
Object Monroe
Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
 E115349 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: Monroe | Statement: [Earl Monroe, familyName, Monroe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monroe
Context triple: [Earl Monroe, familyName, Monroe]
  • A. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • B. Madison
    Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
  • C. Madison
    Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
  • D. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • E. Albany
    Albany is the capital city of the U.S. state of New York, known as a historic political and cultural center in the northeastern United States.
  • 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: Monroe
Triple: [Earl Monroe, familyName, Monroe]
Generated description
Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monroe
Target entity description: Monroe is a surname most famously associated with Earl Monroe, a Hall of Fame American basketball player known for his flashy playing style.
  • A. Monroe
    Monroe is a Chicago 'L' rapid transit station located in the Loop and served by the Chicago Transit Authority's Red Line.
  • B. Madison
    Madison is a common English surname and given name, historically associated with U.S. President James Madison and now widely used as a first name, especially for girls.
  • C. Madison
    Madison is a suburban city in northern Alabama known for its proximity to Huntsville and its strong schools and residential communities.
  • D. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • E. Albany
    Albany is the capital city of the U.S. state of New York, known as a historic political and cultural center in the northeastern United States.
  • 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_69a4939c32488190a7ccd41cf0abb22b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ace5e15c81908cc2e648c9cd52f2 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16f9d07c819097b9cf95d2b708f7 completed March 7, 2026, 12:15 p.m.
NEDg Description generation batch_69ac1a6cee0481908e9e6d7311ee6126 completed March 7, 2026, 12:30 p.m.
NED2 Entity disambiguation (via description) batch_69ac1aebd5d88190830cb66dae2bd0b5 completed March 7, 2026, 12:32 p.m.
Created at: March 1, 2026, 7:39 p.m.