Triple
T21374437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carol Lynley |
E527159
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | The Maltese Bippy |
—
|
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: The Maltese Bippy | Statement: [Carol Lynley, appearedIn, The Maltese Bippy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Maltese Bippy Context triple: [Carol Lynley, appearedIn, The Maltese Bippy]
-
A.
The Maltese Bippy
chosen
The Maltese Bippy is a 1969 horror-comedy film starring Rowan & Martin that parodies mystery and supernatural tropes.
-
B.
Moppet
Moppet is one of the mischievous kitten siblings in Beatrix Potter’s children’s story "The Tale of Tom Kitten."
-
C.
Binky
Binky is a fictional character from the children's animated series "Arthur," known as a tough-looking but kind-hearted bulldog who plays the clarinet.
-
D.
Fay Maltese
Fay Maltese was the first wife of American actor Gene Hackman, with whom she was married for several decades before their divorce.
-
E.
Pippy
Pippy is an educational programming activity for the Sugar learning platform that lets children explore and write simple Python programs.
- 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0b3666c8190a83bb32eeba24105 |
completed | April 22, 2026, 11:27 a.m. |
Created at: April 16, 2026, 5:10 p.m.