Triple
T14714572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tania |
E345642
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Tânia |
E345642
|
NE FINISHED |
How this triple was built (2 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: Tânia | Statement: [Tania, hasSpellingVariant, Tânia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tânia Context triple: [Tania, hasSpellingVariant, Tânia]
-
A.
Lélia
Lélia is a philosophical and romantic novel by George Sand that explores themes of female desire, existential doubt, and social constraint in 19th-century France.
-
B.
Márcia
Márcia is a feminine given name commonly used in Portuguese-speaking countries, derived from the Latin name Marcia.
-
C.
Talita
Talita is a central character in Julio Cortázar’s novel "Rayuela" ("Hopscotch"), known for her enigmatic presence and complex relationships within the bohemian Parisian and Buenos Aires circles depicted in the story.
-
D.
Tania
chosen
Tania is a feminine given name commonly used as a diminutive or variant of names like Tatyana or Tatiana.
-
E.
Eugênia
Eugênia is a Portuguese given name, equivalent to Eugenia, commonly used in Brazil and other Lusophone countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb98513b081908b230f6ac79c72ad |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf0913d6c8190886df4cd0a92aa80 |
completed | May 8, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:29 a.m.