Triple
T292605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bardeen |
E6025
|
entity |
| Predicate | hasNotableScientificAssociation |
P1481
|
FINISHED |
| Object | transistor |
—
|
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: transistor | Statement: [Bardeen, hasNotableScientificAssociation, transistor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableScientificAssociation Context triple: [Bardeen, hasNotableScientificAssociation, transistor]
-
A.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
-
B.
hasNobelLaureatesAffiliated
Indicates that one entity has Nobel Prize laureates formally associated or connected with it (e.g., as members, staff, or alumni).
-
C.
hasNotableHonoree
Indicates that an entity is notably dedicated to, named after, or honors a particular person or group.
-
D.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
-
E.
notablyAssociatedWith
chosen
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea0dd1dc8190aecd5afdeb2fd74b |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e934b4408190b53a17f57a02df65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.