Triple
T18180429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mehmet Oz |
E435264
|
entity |
| Predicate | parentOf |
P120
|
FINISHED |
| Object | Daphne Oz |
—
|
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: Daphne Oz | Statement: [Mehmet Oz, parentOf, Daphne Oz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daphne Oz Context triple: [Mehmet Oz, parentOf, Daphne Oz]
-
A.
Daphne Oz
chosen
Daphne Oz is an American television host, author, and nutrition-focused lifestyle expert known for her work on shows like "The Chew" and various food and wellness programs.
-
B.
Daphne Anderson
Daphne Anderson was a British actress known for her work in mid-20th-century film, television, and theatre, including roles in notable productions such as "The Prince and the Showgirl."
-
C.
Daphne Sullivan
Daphne Sullivan is a wealthy, sharp-witted woman vacationing at a Sicilian luxury resort in the TV series "The White Lotus."
-
D.
Shera Danese
Shera Danese is an American actress best known for her frequent guest appearances on the television series "Columbo" and for being the longtime wife of actor Peter Falk.
-
E.
Tanya Biank
Tanya Biank is an American journalist and author known for her in-depth reporting and books on the lives and challenges of military families.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffa75a081908dad0dcbd736172d |
completed | April 19, 2026, 2 p.m. |
Created at: April 10, 2026, 10:31 a.m.