Triple
T9653366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muppet Babies (2018) |
E233388
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Nanny |
E347342
|
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: Nanny | Statement: [Muppet Babies (2018), featuresCharacter, Nanny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanny Context triple: [Muppet Babies (2018), featuresCharacter, Nanny]
-
A.
Nanny
chosen
Nanny is the kind-hearted, loyal housekeeper who helps care for Pongo and Perdita’s puppies in Disney’s "One Hundred and One Dalmatians."
-
B.
Dayanhe, My Nanny
"Dayanhe, My Nanny" is a well-known poem by Chinese poet Ai Qing that affectionately commemorates the life and kindness of the nanny who raised him.
-
C.
Mr. Nanny
Mr. Nanny is a 1993 family comedy film starring Hulk Hogan as a tough ex-wrestler who becomes the bodyguard and caretaker for two mischievous children.
-
D.
The Nanny
The Nanny is a popular 1990s American sitcom starring Fran Drescher as a flashy Queens nanny working for a wealthy Manhattan family.
-
E.
Nanny and the Professor
Nanny and the Professor is an early-1970s American sitcom about a magical British nanny who brings order and whimsy to a widowed professor’s household and his three children.
- 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bb26b748190bc32e2003829b0ec |
completed | April 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18270dee481909c8d2de1fafdaf5b |
completed | April 4, 2026, 9:28 p.m. |
Created at: March 30, 2026, 8:13 p.m.