Triple
T4628146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Knotts |
E101148
|
entity |
| Predicate | numberOfEmmyAwardsForBarneyFife |
P47170
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Don Knotts, numberOfEmmyAwardsForBarneyFife, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEmmyAwardsForBarneyFife Context triple: [Don Knotts, numberOfEmmyAwardsForBarneyFife, 5]
-
A.
emmyAwardsCount
chosen
Indicates the number of Emmy Awards that an entity has received.
-
B.
emmyAwardFor
Indicates that an entity has received or is associated with a specific Emmy Award for a particular work or achievement.
-
C.
numberOfAcademyAwardsForBestActress
Indicates the total count of Academy Awards received by an entity specifically in the Best Actress category.
-
D.
numberOfTonyAwards
Indicates the total count of Tony Awards that an entity has received.
-
E.
goldenSpikesAwardYear
Indicates the year in which a Golden Spikes Award was given or associated with a particular recipient or event.
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a2e9780819081add547c760abc9 |
completed | March 20, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.