Triple
T14311044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primetime Emmy Award for Outstanding Variety Sketch Series |
E354831
|
entity |
| Predicate | awardCategorySplitYear |
P113715
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Primetime Emmy Award for Outstanding Variety Sketch Series, awardCategorySplitYear, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardCategorySplitYear Context triple: [Primetime Emmy Award for Outstanding Variety Sketch Series, awardCategorySplitYear, 2015]
-
A.
awardReceivedYear
Indicates the specific year in which an entity received a particular award.
-
B.
awardForYear
Indicates that an award is associated with, or was given in, a specific year.
-
C.
numberOfAwardsPerYear
Indicates the number of awards associated with an entity within a given year.
-
D.
AcademyAwardsYear
Indicates the specific year in which the referenced Academy Awards event took place.
-
E.
awardNominationYear
Indicates the year in which an entity received a nomination for an award.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b386d0819087d14f3ce84a1997 |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:12 a.m.