Triple
T18637566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Oxenberg |
E455593
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Oxenberg |
—
|
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: Oxenberg | Statement: [Catherine Oxenberg, familyName, Oxenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oxenberg Context triple: [Catherine Oxenberg, familyName, Oxenberg]
-
A.
Oxenberg
chosen
Oxenberg is a surname most prominently associated with actress Catherine Oxenberg, known for her role on the television series "Dynasty" and her ties to European royalty.
-
B.
Odenberg
Odenberg is a Swedish surname most notably associated with politician Mikael Odenberg.
-
C.
Reisenberg
Reisenberg is a small municipality in Lower Austria’s Baden District, known for its rural character and proximity to Vienna.
-
D.
Turnesa
Turnesa is the surname of a prominent American golfing family that produced several notable professional golfers in the early to mid-20th century.
-
E.
Olesko
Olesko is a historic town in western Ukraine best known for its medieval castle, which served as the birthplace of Polish King John III Sobieski.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc9fa6c81909e1b988bdfb5ebcc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 10, 2026, 11:47 a.m.