Triple
T18637569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Oxenberg |
E455593
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Dynasty |
—
|
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: Dynasty | Statement: [Catherine Oxenberg, notableWork, Dynasty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dynasty Context triple: [Catherine Oxenberg, notableWork, Dynasty]
-
A.
Dynasty
chosen
Dynasty is a popular 1980s American prime-time television soap opera centered on the wealthy and powerful Carrington family.
-
B.
Dynasty
Dynasty is an American R&B and funk group best known for their work with the SOLAR Records label in the late 1970s and 1980s.
-
C.
The Dynasty
The Dynasty is a nonfiction book by Jeff Benedict that chronicles the rise, dominance, and inner workings of the New England Patriots NFL franchise.
-
D.
Dynasties
Dynasties is a BBC nature documentary series that follows individual animal families over time, revealing their complex social structures, struggles, and survival strategies.
-
E.
DYNASTY
DYNASTY is the radio callsign used by China Airlines for its commercial flight operations.
- 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.