Triple
T22472340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emanuele |
E555533
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Emanuela |
—
|
NE NERFINISHED |
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: Emanuela | Statement: [Emanuele, hasFeminineForm, Emanuela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emanuela Context triple: [Emanuele, hasFeminineForm, Emanuela]
-
A.
Emanuela
chosen
Emanuela is a feminine given name, commonly used in various European and Latin cultures, that is a variant of Emmanuelle and ultimately derived from the Hebrew name Emmanuel.
-
B.
Neda
Neda is a coastal municipality in the province of A Coruña, Galicia, Spain, situated along the Ferrol estuary.
-
C.
Juliane
Juliane is a feminine given name, commonly used in various European languages, that is related to and often considered a variant of the name Juliana or Julie.
-
D.
Lucia
Lucia is a feminine given name of Latin origin, commonly associated with light and used in various European cultures.
-
E.
Lale
Lale is a key figure in the British crime drama series "Gangs of London," known for her leadership within a Kurdish militant group and her central role in the show's power struggles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be0d3c08190851537660cda619c |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.