Triple
T30847058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Noces |
E785665
|
entity |
| Predicate | sceneTitle |
P170558
|
FINISHED |
| Object | The Blessing of the Bride |
—
|
NE NERFINISHED |
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: The Blessing of the Bride | Statement: [Les Noces, sceneTitle, The Blessing of the Bride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneTitle Context triple: [Les Noces, sceneTitle, The Blessing of the Bride]
-
A.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
B.
sceneLabel
Indicates the categorical label or type assigned to an entire scene based on its overall content or context.
-
C.
sceneStatus
Indicates the current state or condition of a scene within a given context or process.
-
D.
showsScene
Indicates that one entity (such as a media item or visual representation) depicts or presents a particular scene.
-
E.
sceneFeature
Indicates a characteristic, element, or attribute that is present within or helps define a particular scene.
- F. None of above. chosen
Provenance (4 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6917961ec81908dbd73e67c1ff383 |
completed | May 3, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68fb914b88190b0cad83ea9fe9dfc |
completed | May 2, 2026, 11:58 p.m. |
Created at: April 29, 2026, 8:46 p.m.