Triple
T5317796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Tricks |
E121592
|
entity |
| Predicate | hasSpinOffMerchandise |
P45835
|
FINISHED |
| Object | DVD releases |
—
|
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: DVD releases | Statement: [New Tricks, hasSpinOffMerchandise, DVD releases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpinOffMerchandise Context triple: [New Tricks, hasSpinOffMerchandise, DVD releases]
-
A.
hasMerchandiseTieIn
chosen
Indicates that one entity has a commercial or promotional product or line (merchandise) that is directly tied to, branded with, or derived from another entity.
-
B.
hasSpinOff
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
C.
hasFranchiseOrSpinOff
Indicates that one work, series, or product is related to another as a franchise entry or a spin-off derived from it.
-
D.
hasAnimatedFigures
Indicates that something contains or features figures that are animated or capable of motion.
-
E.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84561c7081909e5937c7816e492c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 1:59 p.m.