Triple
T27781669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beautician and the Beast |
E699347
|
entity |
| Predicate | hasFranDrescherRole |
P167788
|
FINISHED |
| Object | Joy Miller |
—
|
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: Joy Miller | Statement: [The Beautician and the Beast, hasFranDrescherRole, Joy Miller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFranDrescherRole Context triple: [The Beautician and the Beast, hasFranDrescherRole, Joy Miller]
-
A.
characterPlayedByKathleenQuinlan
Indicates that a given character is portrayed or acted by Kathleen Quinlan.
-
B.
roleInTheMarvelousMrsMaisel
Indicates that an entity has a role or appearance in the television series "The Marvelous Mrs. Maisel."
-
C.
characterVoicedBy Debra Messing
Indicates that the character is voiced by Debra Messing.
-
D.
hasRelationshipTypeWith Frank Drebin
Indicates that there exists a specific type of relationship between an entity and Frank Drebin.
-
E.
hasGingerRogersRole
Indicates that an entity is assigned or associated with a role specifically identified as the "Ginger Rogers" role in a given context or production.
- F. None of above. chosen
Provenance (4 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f66cf092c881908d7034c9c2bc61d5 |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 27, 2026, 5:10 p.m.