Triple
T33703014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel (Love Actually) |
E863508
|
entity |
| Predicate | filmSegment |
P150261
|
FINISHED |
| Object | interwoven storyline in ensemble cast |
—
|
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: interwoven storyline in ensemble cast | Statement: [Daniel (Love Actually), filmSegment, interwoven storyline in ensemble cast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSegment Context triple: [Daniel (Love Actually), filmSegment, interwoven storyline in ensemble cast]
-
A.
filmSceneType
Indicates the type or category of a scene within a film, such as its narrative function, style, or setting.
-
B.
filmicFunction
Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
-
C.
filmContent
chosen
Indicates that one entity is the substantive material or subject matter contained within a film.
-
D.
filmAbility
Indicates that one entity has the capability or skill to create, direct, or otherwise produce films involving another entity.
-
E.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:43 a.m.