Triple

T14107448
Position Surface form Disambiguated ID Type / Status
Subject How the Leopard Got His Spots E339542 entity
Predicate fictionalHumanCharacter P43063 FINISHED
Object Ethiopian E263902 NE FINISHED

How this triple was built (3 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: Ethiopian | Statement: [How the Leopard Got His Spots, fictionalHumanCharacter, Ethiopian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ethiopian
Context triple: [How the Leopard Got His Spots, fictionalHumanCharacter, Ethiopian]
  • A. Ethiopian chosen
    Ethiopian refers to a person from Ethiopia or of Ethiopian descent, associated with the country's distinct cultures, languages, and history in the Horn of Africa.
  • B. ETHIOPIAN
    ETHIOPIAN is the radio callsign used by Ethiopian Airlines for its flight operations and air traffic communications.
  • C. Eritrean
    Eritrean refers to someone or something originating from Eritrea, a country in the Horn of Africa known for its diverse ethnic groups and Red Sea coastline.
  • D. Oromo
    Oromo is a Cushitic language widely spoken by the Oromo people, primarily in Ethiopia and parts of neighboring East African countries.
  • E. Amharic
    Amharic is a Semitic language widely spoken in Ethiopia and used as a major language of government, education, and media in the country.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalHumanCharacter
Context triple: [How the Leopard Got His Spots, fictionalHumanCharacter, Ethiopian]
  • A. fictionalCharacter
    Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
  • B. fictionalCharacterFrom chosen
    Indicates that a fictional character originates from, or is created within, a particular work, universe, or source.
  • C. fictionalEntityType
    Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
  • D. fictionalPlayer
    Indicates that the referenced player entity is imaginary or does not exist in the real world, but is instead part of a fictional or simulated context.
  • E. fictionalCharacterAssociatedWith
    Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
  • F. None of above.

Provenance (4 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600ada808190b92d67dc30f13d15 completed April 14, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf04871c8190891605415f1abf7f completed May 7, 2026, 6:50 p.m.
PD Predicate disambiguation batch_69de05b2f7e481908a9a7d40153234c0 completed April 14, 2026, 9:15 a.m.
Created at: April 9, 2026, 10:22 p.m.