Triple
T25315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE John von Neumann Medal |
E505
|
entity |
| Predicate | hasAwardingBodyType |
P1497
|
FINISHED |
| Object | professional association |
—
|
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: professional association | Statement: [IEEE John von Neumann Medal, hasAwardingBodyType, professional association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardingBodyType Context triple: [IEEE John von Neumann Medal, hasAwardingBodyType, professional association]
-
A.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
B.
awardStatus
Indicates the current state or outcome of an award in relation to an entity, such as whether it has been granted, pending, rejected, or completed.
-
C.
isTheHighestAwardOf
Indicates that one award is the most prestigious or top-ranking honor within a particular field, organization, or context.
-
D.
typicalAwardComponents
Indicates the standard elements or parts that commonly make up a particular award.
-
E.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246d6aca88190a86b7c41d497bacd |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.