Triple
T8375882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Tinker |
E197572
|
entity |
| Predicate | appearsInEpisodeFormat |
P795
|
FINISHED |
| Object | Christmas specials of The Vicar of Dibley |
—
|
LITERAL 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: Christmas specials of The Vicar of Dibley | Statement: [Alice Tinker, appearsInEpisodeFormat, Christmas specials of The Vicar of Dibley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInEpisodeFormat Context triple: [Alice Tinker, appearsInEpisodeFormat, Christmas specials of The Vicar of Dibley]
-
A.
appearsInSeries
Indicates that an entity is featured or occurs within a particular series.
-
B.
appearsInSeriesBy
Indicates that one entity (such as a work or character) is featured within a series that is created, authored, or produced by another entity.
-
C.
appearsIn
chosen
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
D.
appearsInAdaptationBy
Indicates that an entity is featured or present in an adaptation created by a specified adapter (e.g., author, director, or studio).
-
E.
associatedEpisode
Indicates that one entity is linked or connected to a particular episode as its related or relevant installment.
- F. None of above.
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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80bf6b8081909b98762b1f900bef |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cd04b08190ab5f72afd22a7967 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:01 p.m.