Triple
T3575905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexanderson |
E75686
|
entity |
| Predicate | hasNotableFieldAssociation |
P39276
|
FINISHED |
| Object | radio technology |
—
|
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: radio technology | Statement: [Alexanderson, hasNotableFieldAssociation, radio technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldAssociation Context triple: [Alexanderson, hasNotableFieldAssociation, radio technology]
-
A.
hasNotableType
Indicates that an entity is associated with a specific notable category or type that characterizes its significance or role.
-
B.
hasNotableConnectionTo
Indicates a significant or noteworthy relationship, association, or link exists between two entities.
-
C.
hasNotableAffiliation
Indicates that an entity is significantly associated or connected with another entity, such as an organization, group, or institution, in a way that is noteworthy or distinguished.
-
D.
hasNotableRelativeGroup
Indicates that an entity is associated with a group of relatives who are notable or significant in some recognized way.
-
E.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0da77008190922f414b85b9cad4 |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.