Triple
T4390496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States daytime television industry |
E99348
|
entity |
| Predicate | historicallyImportantGenre |
P56333
|
FINISHED |
| Object | daytime soap opera |
—
|
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: daytime soap opera | Statement: [United States daytime television industry, historicallyImportantGenre, daytime soap opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicallyImportantGenre Context triple: [United States daytime television industry, historicallyImportantGenre, daytime soap opera]
-
A.
historicalGenre
Indicates that something belongs to or is categorized within a particular historical genre.
-
B.
historicalCategory
Indicates that an entity is classified within a particular historical grouping, period, or type based on its time-related characteristics or context.
-
C.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
D.
formerGenreFocus
Indicates that an entity previously concentrated on or specialized in a particular genre, but no longer does so.
-
E.
influencedByGenre
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352843d7c8190929b94c94eaa63df |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:19 p.m.