Triple
T21780126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliana |
E537687
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Juliane |
—
|
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: Juliane | Statement: [Juliana, hasVariant, Juliane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juliane Context triple: [Juliana, hasVariant, Juliane]
-
A.
Juliane
chosen
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.
-
B.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
-
C.
Annemarie
Annemarie is a feminine given name of German origin, often used in German-speaking and other European countries.
-
D.
Emanuela
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.
-
E.
Azaria
Azaria is a given name used by various individuals, including the Israeli engineer and academic Azaria Paz.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0462cae6481908d3e7f71683d8921 |
completed | April 28, 2026, 5:31 a.m. |
Created at: April 16, 2026, 6:52 p.m.