Triple
T10442488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadia |
E246202
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Nadiya |
E616360
|
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: Nadiya | Statement: [Nadia, hasVariant, Nadiya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nadiya Context triple: [Nadia, hasVariant, Nadiya]
-
A.
Nadya
chosen
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
-
B.
Anisa
Anisa is a feminine given name of Arabic origin commonly used in various Muslim-majority cultures.
-
C.
Naila
Naila is a small town in northern Bavaria, Germany, known for its location near the Franconian Forest and its traditional Upper Franconian character.
-
D.
Anika
Anika is the first name of Anika Noni Rose, an American actress and singer best known for voicing Tiana in Disney’s "The Princess and the Frog."
-
E.
Nita
Nita is a feminine given name commonly used as a shortened or affectionate form of longer names such as Juanita.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbd731c819084dfff83b4481ae8 |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89fa5b3b081909af7de1745372add |
completed | April 10, 2026, 6:58 a.m. |
Created at: April 6, 2026, 12:15 p.m.