Triple

T12654154
Position Surface form Disambiguated ID Type / Status
Subject Fante language E302238 entity
Predicate hasAlternativeName P39 FINISHED
Object Fanti
Fanti is a dialect of the Akan language spoken primarily by the Fante people in coastal Ghana.
E996657 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: Fanti | Statement: [Fante language, hasAlternativeName, Fanti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fanti
Context triple: [Fante language, hasAlternativeName, Fanti]
  • A. Limal
    Limal is a residential district and former village within the city of Wavre in Walloon Brabant, Belgium.
  • B. Lali
    Lali is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Lulu
    Lulu is a central character in the 1999 British cult film "Human Traffic," which explores the lives and clubbing culture of young people in Cardiff.
  • E. Lulu
    Lulu is the central character in Harold Pinter’s play "The Birthday Party," around whom the play’s unsettling and ambiguous events revolve.
  • 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: Fanti
Triple: [Fante language, hasAlternativeName, Fanti]
Generated description
Fanti is a dialect of the Akan language spoken primarily by the Fante people in coastal Ghana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fanti
Target entity description: Fanti is a dialect of the Akan language spoken primarily by the Fante people in coastal Ghana.
  • A. Limal
    Limal is a residential district and former village within the city of Wavre in Walloon Brabant, Belgium.
  • B. Lali
    Lali is the official mascot character created for the 2017 World Aquatics Championships held in Budapest.
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Lulu
    Lulu is a central character in the 1999 British cult film "Human Traffic," which explores the lives and clubbing culture of young people in Cardiff.
  • E. Lulu
    Lulu is the central character in Harold Pinter’s play "The Birthday Party," around whom the play’s unsettling and ambiguous events revolve.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96160730c81909e1aa3efb51bf159 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6688104d48190939933b93b7e60cc completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f66c572f848190a8cad6311d3315a3 completed May 2, 2026, 9:27 p.m.
NED2 Entity disambiguation (via description) batch_69f66cef79148190a052fb9ade3b0d27 completed May 2, 2026, 9:30 p.m.
Created at: April 9, 2026, 5:18 p.m.