Triple
T15054614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maddalena Orsini |
E379454
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maddalena |
E201622
|
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: Maddalena | Statement: [Maddalena Orsini, givenName, Maddalena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maddalena Context triple: [Maddalena Orsini, givenName, Maddalena]
-
A.
Maddalena
chosen
Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
-
B.
Madalena
Madalena is a coastal town on the Azorean island of Pico in Portugal, known as a gateway to Mount Pico and for its wine culture and maritime heritage.
-
C.
Madalena
Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
-
D.
Ginoria
Ginoria is a small genus of flowering plants in the loosestrife family, Lythraceae, known for its shrubby species native to the Caribbean and nearby regions.
-
E.
Lodoletta
Lodoletta is an opera in three acts by Italian composer Pietro Mascagni, known for its verismo style and tragic love story.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda92091c81909180f486edf01405 |
completed | April 15, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5bdeee48190949b0fe63eb6a21a |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 3:01 a.m.