Triple
T15949854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | We TV |
E386785
|
entity |
| Predicate | typicalContentTheme |
P7671
|
FINISHED |
| Object | marriage and weddings |
—
|
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: marriage and weddings | Statement: [We TV, typicalContentTheme, marriage and weddings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalContentTheme Context triple: [We TV, typicalContentTheme, marriage and weddings]
-
A.
tacklesTheme
Indicates that one entity addresses, explores, or deals with a particular theme as a central subject.
-
B.
thematicConcept
Indicates that one entity embodies, expresses, or is centrally concerned with a particular underlying theme or conceptual idea represented by the other entity.
-
C.
culturalThemes
Indicates that there is a relationship between entities where one embodies, expresses, or is associated with particular cultural themes present in or derived from the other.
-
D.
themeHighlights
Indicates that certain elements are emphasized or visually distinguished as key features within a particular theme.
-
E.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.