Triple
T33599330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliet (Love Actually) |
E860671
|
entity |
| Predicate | weddingVideoSceneType |
P86909
|
FINISHED |
| Object | iconic wedding video storyline |
—
|
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: iconic wedding video storyline | Statement: [Juliet (Love Actually), weddingVideoSceneType, iconic wedding video storyline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weddingVideoSceneType Context triple: [Juliet (Love Actually), weddingVideoSceneType, iconic wedding video storyline]
-
A.
filmSceneType
chosen
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
B.
hasWeddingSceneWith
Indicates that two entities appear together in a wedding scene within the same context or work.
-
C.
weddingPart
Indicates that an entity participates as a component or role within a wedding event.
-
D.
scenes
Indicates that one entity is a scene or setting in which the other entity occurs, appears, or is depicted.
-
E.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:41 a.m.