Triple

T23004034
Position Surface form Disambiguated ID Type / Status
Subject Africa! exhibit E572709 entity
Predicate city P40 FINISHED
Object Toledo
Toledo is a historic city in northwestern Ohio, United States, known for its glass industry, port on Lake Erie, and cultural institutions.
 E25661 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: Toledo | Statement: [Africa! exhibit, city, Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toledo
Context triple: [Africa! exhibit, city, Toledo]
  • A. Toledo
    Toledo is a Spanish-origin surname borne by various notable individuals across fields such as sports, politics, and the arts.
  • B. Toledo
    Toledo is a historic Spanish city renowned for its medieval architecture, cultural heritage, and role as a major political and religious center in Spain’s history.
  • C. Toledo
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • D. Toledo
    Toledo is a small village in east-central Illinois that serves as the administrative and commercial hub of Cumberland County.
  • E. Toledo City
    Toledo City is a coastal component city on the western side of Cebu Island in the Philippines, known for its mining industry and port facilities.
  • 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: Toledo
Triple: [Africa! exhibit, city, Toledo]
Generated description
Toledo is a historic city in northwestern Ohio, United States, known for its glass industry, port on Lake Erie, and cultural institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toledo
Target entity description: Toledo is a historic city in northwestern Ohio, United States, known for its glass industry, port on Lake Erie, and cultural institutions.
  • A. Toledo
    Toledo is a historic Spanish city renowned for its medieval architecture, cultural heritage, and role as a major political and religious center in Spain’s history.
  • B. Toledo chosen
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • C. Toledo
    Toledo is a small village in east-central Illinois that serves as the administrative and commercial hub of Cumberland County.
  • D. Toledo
    Toledo is a Spanish-origin surname borne by various notable individuals across fields such as sports, politics, and the arts.
  • E. Toledo City
    Toledo City is a coastal component city on the western side of Cebu Island in the Philippines, known for its mining industry and port facilities.
  • F. None of above.

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_69e245b6a3ac81908087599eefe3e365 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183556cd08190b18780680bc4f23e completed April 29, 2026, 4:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bf2a2754c8190bccf743d66db9242 completed May 19, 2026, 5:18 a.m.
NEDg Description generation batch_6a0bf44ceb288190a6741635c9ee2e1f completed May 19, 2026, 5:25 a.m.
NED2 Entity disambiguation (via description) batch_6a0bf4a68f8c8190a922ff9d23b57831 completed May 19, 2026, 5:27 a.m.
Created at: April 17, 2026, 3:51 p.m.