Triple
T2875850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kia Nurse |
E56875
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nurse |
E3911
|
NE FINISHED |
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: Nurse | Statement: [Kia Nurse, familyName, Nurse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nurse Context triple: [Kia Nurse, familyName, Nurse]
-
A.
Nurse
chosen
Nurse is a common English occupational surname originally referring to someone who worked as a caregiver or medical attendant.
-
B.
Nurses
Nurses is an American sitcom that follows the personal and professional lives of a group of nurses working at a Miami hospital.
-
C.
RN
RN is the commonly used abbreviation for "RN: The Memoirs of Richard Nixon," the former U.S. president’s autobiographical account of his life and political career.
-
D.
Nurse Matilda
Nurse Matilda is the magical, stern-yet-kind nanny from Christianna Brand’s children’s books that inspired the film character Nanny McPhee.
-
E.
Richard Nurse
Richard Nurse is a Canadian former professional ice hockey player who competed in the World Hockey Association during the 1970s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe0061d048190bb1e5a01e7ceb0e2 |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01dbb28588190ba2daae192744908 |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:03 p.m.