Triple
T10180884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laetitia |
E236777
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Letitia |
E289047
|
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: Letitia | Statement: [Laetitia, hasVariant, Letitia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Letitia Context triple: [Laetitia, hasVariant, Letitia]
-
A.
Letitia
chosen
Letitia is a feminine given name of Latin origin, commonly associated with the meaning "joy" or "happiness."
-
B.
Letitia Cropley
Letitia Cropley is an eccentric parishioner in the British sitcom "The Vicar of Dibley," best known for her bizarre and unappetizing culinary creations.
-
C.
Lucyana
Lucyana is a feminine given name, typically considered a variant spelling of Luciana and related names like Lucía and Lucy.
-
D.
Georgiana
Georgiana is a feminine given name of Greek origin, often associated with elegance and historically borne by various notable women in British and European society.
-
E.
Katherine
Katherine is one of the witty noblewomen in William Shakespeare’s comedy "Love’s Labour’s Lost," known for her sharp dialogue and role in the play’s romantic entanglements.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded315f14819085727bd9b4363d10 |
completed | April 2, 2026, 4:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d301373a008190b8d39a8db4167e4f |
completed | April 6, 2026, 12:41 a.m. |
Created at: March 30, 2026, 9:11 p.m.