Triple

T4163626
Position Surface form Disambiguated ID Type / Status
Subject Sheila E84388 entity
Predicate hasAlternativeSpelling P457 FINISHED
Object Sheyla
Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
 E419348 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: Sheyla | Statement: [Sheila, hasAlternativeSpelling, Sheyla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sheyla
Context triple: [Sheila, hasAlternativeSpelling, Sheyla]
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Yovanna
    Yovanna is a fictional character played by actress Adria Arjona, known from her work in film and television.
  • C. Haydée
    Haydée is a fictional Greek princess and former slave who becomes a devoted ally and love interest of Edmond Dantès in Alexandre Dumas' novel "The Count of Monte Cristo."
  • D. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • E. Adailiya
    Adailiya is a residential district in Kuwait City known for its embassies, sports facilities, and central location within the capital.
  • 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: Sheyla
Triple: [Sheila, hasAlternativeSpelling, Sheyla]
Generated description
Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sheyla
Target entity description: Sheyla is a feminine given name, typically considered a variant of Sheila or Shayla and used in various cultures.
  • A. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • B. Yovanna
    Yovanna is a fictional character played by actress Adria Arjona, known from her work in film and television.
  • C. Haydée
    Haydée is a fictional Greek princess and former slave who becomes a devoted ally and love interest of Edmond Dantès in Alexandre Dumas' novel "The Count of Monte Cristo."
  • D. Alejandra
    Alejandra is the feminine given name corresponding to Alejandro, commonly used in Spanish-speaking cultures.
  • E. Adailiya
    Adailiya is a residential district in Kuwait City known for its embassies, sports facilities, and central location within the capital.
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02a9bf348190b99cecd19fe65779 completed March 9, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589ec8a60819099647577b7ab9be1 completed March 14, 2026, 4:16 p.m.
NEDg Description generation batch_69b58b22a1d88190a16e1c1e41291f5a completed March 14, 2026, 4:21 p.m.
NED2 Entity disambiguation (via description) batch_69b58b8bfb288190a097942b5b8c366e completed March 14, 2026, 4:23 p.m.
Created at: March 9, 2026, 3:44 p.m.