Triple
T29273811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carry On Sergeant |
E742193
|
entity |
| Predicate | filmSeriesDebutOf |
P20449
|
FINISHED |
| Object | Carry On franchise |
—
|
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: Carry On franchise | Statement: [Carry On Sergeant, filmSeriesDebutOf, Carry On franchise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSeriesDebutOf Context triple: [Carry On Sergeant, filmSeriesDebutOf, Carry On franchise]
-
A.
filmSeriesDebutYear
Indicates the calendar year in which a film series was first released or made its initial debut.
-
B.
filmSeriesStart
chosen
Indicates that a particular film marks the beginning or first installment of a film series.
-
C.
seriesDebut
Indicates the first appearance or initial release of a series in which the subject entity is introduced.
-
D.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
-
E.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
- 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_69f0912124d48190a046642b69407f4c |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f664e60540819095ecf1d422f2f406 |
completed | May 2, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 12:49 p.m.