Triple

T10703097
Position Surface form Disambiguated ID Type / Status
Subject Tiffani E252327 entity
Predicate hasSpellingVariant P457 FINISHED
Object Tifanie
Tifanie is a given name, typically a feminine variant of the name Tiffany.
 E881536 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: Tifanie | Statement: [Tiffani, hasSpellingVariant, Tifanie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tifanie
Context triple: [Tiffani, hasSpellingVariant, Tifanie]
  • A. Tania
    Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
  • B. Tonia
    Tonia is a feminine given name, typically used as a short form of Antonia.
  • C. Tinée
    Tinée is a river in southeastern France that flows through the Alpes-Maritimes department in the Provence-Alpes-Côte d'Azur region.
  • D. Ta’aisha
    The Ta’aisha are a Sudanese Arab tribal group from the Darfur–Kordofan region, historically prominent through their leadership role in the Mahdist state under Abdallahi ibn Muhammad.
  • E. Terêna
    Terêna is an Arawakan language spoken by the Terena Indigenous people of Brazil, primarily in the state of Mato Grosso do Sul.
  • 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: Tifanie
Triple: [Tiffani, hasSpellingVariant, Tifanie]
Generated description
Tifanie is a given name, typically a feminine variant of the name Tiffany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tifanie
Target entity description: Tifanie is a given name, typically a feminine variant of the name Tiffany.
  • A. Tania
    Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
  • B. Tonia
    Tonia is a feminine given name, typically used as a short form of Antonia.
  • C. Tinée
    Tinée is a river in southeastern France that flows through the Alpes-Maritimes department in the Provence-Alpes-Côte d'Azur region.
  • D. Ta’aisha
    The Ta’aisha are a Sudanese Arab tribal group from the Darfur–Kordofan region, historically prominent through their leadership role in the Mahdist state under Abdallahi ibn Muhammad.
  • E. Terêna
    Terêna is an Arawakan language spoken by the Terena Indigenous people of Brazil, primarily in the state of Mato Grosso do Sul.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fddd28d481908abc5c1d4e5a9f3e completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbad110d9481908c3c0873424ec616 completed April 12, 2026, 2:32 p.m.
NEDg Description generation batch_69dbaeb211088190a9118c71918584e5 completed April 12, 2026, 2:39 p.m.
NED2 Entity disambiguation (via description) batch_69dbaf7c999c819097a8cdf5bd82f648 completed April 12, 2026, 2:43 p.m.
Created at: April 8, 2026, 9:12 p.m.