Triple
T1287913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tramp |
E27476
|
entity |
| Predicate | notableSceneType |
P22727
|
FINISHED |
| Object | chase sequences |
—
|
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: chase sequences | Statement: [The Tramp, notableSceneType, chase sequences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSceneType Context triple: [The Tramp, notableSceneType, chase sequences]
-
A.
notableScene
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
-
C.
notableSegmentType
chosen
Indicates that a particular segment or portion of something is classified as being of notable or special significance by its type.
-
D.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
E.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d38d7c81908941edda9cac5d6a |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.