Triple
T20493558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleonor Magdalene of Neuburg |
E502808
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Eleonor |
—
|
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: Eleonor | Statement: [Eleonor Magdalene of Neuburg, givenName, Eleonor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eleonor Context triple: [Eleonor Magdalene of Neuburg, givenName, Eleonor]
-
A.
Eleonor Magdalene
chosen
Eleonor Magdalene was a 17th–18th century Holy Roman Empress and Queen of Hungary and Bohemia, known for her piety and influence at the Habsburg court.
-
B.
Eleonore
Eleonore is the given first name of Hannelore Kohl, the late wife of former German Chancellor Helmut Kohl.
-
C.
Eleanor
Eleanor is the daughter of American model and actress Devon Aoki.
-
D.
Eleanor
Eleanor is a feminine given name most famously borne by Eleanor Roosevelt, the influential First Lady of the United States and human rights advocate.
-
E.
Eleanor
Eleanor was one of the merchant ships in Boston Harbor whose tea cargo was destroyed during the Boston Tea Party protest against British taxation in 1773.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbc58d08190bf3f6b60259a8be1 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.