Triple
T4577598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midsomer Murders |
E123175
|
entity |
| Predicate | hasSpinOffMedia |
P45612
|
FINISHED |
| Object | novel tie-ins |
—
|
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: novel tie-ins | Statement: [Midsomer Murders, hasSpinOffMedia, novel tie-ins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpinOffMedia Context triple: [Midsomer Murders, hasSpinOffMedia, novel tie-ins]
-
A.
hasSpinOff
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
B.
hasFranchiseOrSpinOff
chosen
Indicates that one work, series, or product is related to another as a franchise entry or a spin-off derived from it.
-
C.
hasMediaFranchise
Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
-
D.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
-
E.
spinoffAppearance
Indicates that an entity appears in a derivative or spinoff work related to another original work or series.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58e153908190ac8f578e03aecdfc |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.