Triple

T3364254
Position Surface form Disambiguated ID Type / Status
Subject Ban Johnson E70796 entity
Predicate nickname P55 FINISHED
Object Ban
Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
 E351072 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: Ban | Statement: [Ban Johnson, nickname, Ban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ban
Context triple: [Ban Johnson, nickname, Ban]
  • A. Bar
    Bar is a coastal city and major seaport in southern Montenegro on the Adriatic Sea.
  • B. Bal
    Bal is the given name of Bal Gangadhar Tilak, a prominent Indian nationalist leader and social reformer of the late 19th and early 20th centuries.
  • C. Bas
    Bas is a Sudanese-American rapper and songwriter from Queens, New York, best known as a Dreamville Records artist and frequent collaborator of J. Cole.
  • D. Bo
    Bo was an extinct indigenous language of the Great Andamanese people, once spoken in the Andaman Islands of India.
  • E. Bo
    Bo is the widely known nickname of legendary American college football coach Bo Schembechler, famed for his long tenure at the University of Michigan.
  • 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: Ban
Triple: [Ban Johnson, nickname, Ban]
Generated description
Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ban
Target entity description: Ban was the nickname of Ban Johnson, the influential early 20th-century baseball executive who served as the first president of the American League.
  • A. Bar
    Bar is a coastal city and major seaport in southern Montenegro on the Adriatic Sea.
  • B. Bal
    Bal is the given name of Bal Gangadhar Tilak, a prominent Indian nationalist leader and social reformer of the late 19th and early 20th centuries.
  • C. Bas
    Bas is a Sudanese-American rapper and songwriter from Queens, New York, best known as a Dreamville Records artist and frequent collaborator of J. Cole.
  • D. Bo
    Bo was an extinct indigenous language of the Great Andamanese people, once spoken in the Andaman Islands of India.
  • E. Bo
    Bo is the widely known nickname of legendary American college football coach Bo Schembechler, famed for his long tenure at the University of Michigan.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb28467b88190bdf70b851bc8efa9 completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3254daf8c8190b2141682503c111e completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b326f94db481908560b64f701dd433 completed March 12, 2026, 8:50 p.m.
NED2 Entity disambiguation (via description) batch_69b3276b55a0819094face2e56001921 completed March 12, 2026, 8:51 p.m.
Created at: March 8, 2026, 3:13 p.m.