Triple
T15632386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Pink |
E375846
|
entity |
| Predicate | sceneFeaturedIn |
P626
|
FINISHED |
| Object | opening diner scene in Reservoir Dogs |
—
|
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: opening diner scene in Reservoir Dogs | Statement: [Mr. Pink, sceneFeaturedIn, opening diner scene in Reservoir Dogs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneFeaturedIn Context triple: [Mr. Pink, sceneFeaturedIn, opening diner scene in Reservoir Dogs]
-
A.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
-
B.
settingOfWorkFeaturedIn
Indicates that a place or environment serves as the primary setting where the events of a creative work take place.
-
C.
featuredIn
chosen
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
-
D.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
E.
bestSeenIn
Indicates that something is most effectively or appropriately experienced, observed, or appreciated within a particular context, medium, or setting.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.