Triple

T10454199
Position Surface form Disambiguated ID Type / Status
Subject Tabitha E246507 entity
Predicate hasVariant P455 FINISHED
Object Tabita
Tabita is a feminine given name, commonly considered a variant of Tabitha and used in various cultures.
 E863534 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: Tabita | Statement: [Tabitha, hasVariant, Tabita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tabita
Context triple: [Tabitha, hasVariant, Tabita]
  • A. 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.
  • B. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • C. Tabaiba
    Tabaiba is a coastal residential village on the island of Tenerife in Spain’s Canary Islands, known for its seaside setting and proximity to the municipality of El Rosario.
  • D. Amandina
    Amandina is a feminine given name that functions as a variant form of Amanda.
  • E. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • 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: Tabita
Triple: [Tabitha, hasVariant, Tabita]
Generated description
Tabita is a feminine given name, commonly considered a variant of Tabitha and used in various cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tabita
Target entity description: Tabita is a feminine given name, commonly considered a variant of Tabitha and used in various cultures.
  • A. 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.
  • B. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • C. Tabaiba
    Tabaiba is a coastal residential village on the island of Tenerife in Spain’s Canary Islands, known for its seaside setting and proximity to the municipality of El Rosario.
  • D. Amandina
    Amandina is a feminine given name that functions as a variant form of Amanda.
  • E. Sheilia
    Sheilia is a feminine given name, typically considered an alternative spelling of the name Sheila.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe47fee48190b38ec0466ff0165a completed April 7, 2026, 12:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87f07c9f48190b0fce7740a2e003a completed April 10, 2026, 4:39 a.m.
NEDg Description generation batch_69d886c562c081908aae846da8efb1a5 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dce21448190b093b4f548e29f84 completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 12:17 p.m.