Triple
T5110453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nurse Matilda |
E115200
|
entity |
| Predicate | appearsInWork |
P795
|
FINISHED |
| Object | Nurse Matilda |
E115200
|
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 Matilda | Statement: [Nurse Matilda, appearsInWork, Nurse Matilda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nurse Matilda Context triple: [Nurse Matilda, appearsInWork, Nurse Matilda]
-
A.
Nurse Matilda
chosen
Nurse Matilda is the magical, stern-yet-kind nanny from Christianna Brand’s children’s books that inspired the film character Nanny McPhee.
-
B.
Edna Murphy
Edna Murphy was an American silent film actress active in the 1920s, known for her roles in numerous melodramas and comedies.
-
C.
Dolly Sharp
Dolly Sharp was an American adult film actress best known for her role in the landmark 1972 pornographic film "Deep Throat."
-
D.
Madame Foster
Madame Foster is the eccentric, kind-hearted elderly founder and caretaker of the whimsical residence for imaginary friends in the animated series "Foster's Home for Imaginary Friends."
-
E.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ad362c8190b9cbded390aaea3c |
completed | March 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bebaa719748190930dceaeedb346c2 |
completed | March 21, 2026, 3:35 p.m. |
Created at: March 20, 2026, 1:41 p.m.