Triple

T8318746
Position Surface form Disambiguated ID Type / Status
Subject The American Spelling Book E194773 entity
Predicate publisher P29 FINISHED
Object Hudson and Goodwin
Hudson and Goodwin was an early American publishing firm known for issuing influential educational works in the late 18th and early 19th centuries.
 E725756 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: Hudson and Goodwin | Statement: [The American Spelling Book, publisher, Hudson and Goodwin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hudson and Goodwin
Context triple: [The American Spelling Book, publisher, Hudson and Goodwin]
  • A. Bancroft
    Bancroft is an English-origin surname borne by various notable figures in politics, academia, and the arts.
  • B. Goode
    Goode is an English surname borne by various notable individuals across fields such as acting, politics, and academia.
  • C. The Allen
    The Allen is the commonly used local name for Allen Road, a major expressway in Toronto, Ontario, Canada.
  • D. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • E. Ayers-Allen
    Ayers-Allen is the hyphenated surname of American actress Phylicia Rashad, used earlier in her career before she adopted her current professional name.
  • 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: Hudson and Goodwin
Triple: [The American Spelling Book, publisher, Hudson and Goodwin]
Generated description
Hudson and Goodwin was an early American publishing firm known for issuing influential educational works in the late 18th and early 19th centuries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hudson and Goodwin
Target entity description: Hudson and Goodwin was an early American publishing firm known for issuing influential educational works in the late 18th and early 19th centuries.
  • A. Bancroft
    Bancroft is an English-origin surname borne by various notable figures in politics, academia, and the arts.
  • B. Goode
    Goode is an English surname borne by various notable individuals across fields such as acting, politics, and academia.
  • C. The Allen
    The Allen is the commonly used local name for Allen Road, a major expressway in Toronto, Ontario, Canada.
  • D. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • E. Ayers-Allen
    Ayers-Allen is the hyphenated surname of American actress Phylicia Rashad, used earlier in her career before she adopted her current professional name.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f648e10819081ad1fed870b2b86 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd9596891c81909296050d0a8117ca completed April 1, 2026, 10 p.m.
NEDg Description generation batch_69cdab5f30b0819080136084d81774a9 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2d365e48190a766ca959ce56b19 completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:55 p.m.