Triple
T26918403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gallopin' Gaucho |
E677575
|
entity |
| Predicate | hasDanceScene |
P85248
|
FINISHED |
| Object | Mickey and Minnie dancing in the cantina |
—
|
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: Mickey and Minnie dancing in the cantina | Statement: [The Gallopin' Gaucho, hasDanceScene, Mickey and Minnie dancing in the cantina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDanceScene Context triple: [The Gallopin' Gaucho, hasDanceScene, Mickey and Minnie dancing in the cantina]
-
A.
hasDanceSceneWith
chosen
Indicates that two entities participate together in a dance scene within the same context or work.
-
B.
hasDanceSequences
Indicates that the subject contains or features one or more dance sequences as part of its content or activity.
-
C.
hasDanceChoreography
Indicates that an entity is associated with or characterized by a specific dance choreography.
-
D.
hasDanceMovement
Indicates that one entity includes, performs, or is characterized by a specific dance movement associated with another entity.
-
E.
hasChoreographedDanceInVideo
Indicates that an entity has created or arranged the choreography for a dance that appears in a particular video.
- 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_69eee9bdebc48190ba90a12a63e09c73 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 6:05 a.m.