Triple
T9085682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felicia |
E217747
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Felicitas |
E262440
|
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: Felicitas | Statement: [Felicia, hasVariant, Felicitas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Felicitas Context triple: [Felicia, hasVariant, Felicitas]
-
A.
Felicitas
chosen
Felicitas is a feminine given name of Latin origin, associated with good fortune and happiness and historically linked to the Roman goddess of luck and success.
-
B.
Marcellina
Marcellina is a small Italian municipality in the Lazio region, situated near Rome in the province of Rome.
-
C.
Erminia
Erminia is a compassionate and conflicted princess in Torquato Tasso’s epic poem "Gerusalemme liberata," known for her unrequited love for the Christian knight Tancredi and her dramatic flight from the battlefield.
-
D.
Tullia
Tullia was the daughter of the Roman statesman and orator Marcus Tullius Cicero and his first wife, Terentia.
-
E.
Pamona
Pamona is an Austronesian language spoken by the Pamona people of Central Sulawesi, Indonesia.
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc960d0b008190b0e9e61fac45101d |
completed | April 1, 2026, 3:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffe40823481909a5c4b82bd24293a |
completed | April 3, 2026, 5:52 p.m. |
Created at: March 30, 2026, 7:13 p.m.