Triple
T32747146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver Snoopy Award |
E837384
|
entity |
| Predicate | maximumRecipientsPerYear |
P187592
|
FINISHED |
| Object | small percentage of eligible workforce |
—
|
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: small percentage of eligible workforce | Statement: [Silver Snoopy Award, maximumRecipientsPerYear, small percentage of eligible workforce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumRecipientsPerYear Context triple: [Silver Snoopy Award, maximumRecipientsPerYear, small percentage of eligible workforce]
-
A.
formerMaximumNumberOfRecipientsPerYear
Indicates the maximum number of recipients allowed per year under a previous or no-longer-current rule or configuration.
-
B.
maximumNumberOfRecipientsPerAward
Indicates the largest number of recipients that can share or receive a single award.
-
C.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
-
D.
maximumLivingRecipientsAtATime
Indicates the greatest number of living recipients that can simultaneously hold or benefit from a given thing, status, or allocation at any one time.
-
E.
numberOfRecipientsPerMonth
Indicates the quantity of recipients associated with an entity for each month.
- 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_69f34936e1748190b797e406e4e9293a |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb6fdab95c81909acff3c6a2359787 |
completed | May 6, 2026, 4:44 p.m. |
Created at: May 1, 2026, 1:12 a.m.