Triple
T24739382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1946 Georgia gubernatorial election |
E618508
|
entity |
| Predicate | usedWhitePrimary |
P157072
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [1946 Georgia gubernatorial election, usedWhitePrimary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedWhitePrimary Context triple: [1946 Georgia gubernatorial election, usedWhitePrimary, true]
-
A.
primaryWhiteVariety
Indicates that one entity is the primary white (light-skinned or white-colored) variety or form of another entity.
-
B.
primaryColour
Indicates that one entity is the main or dominant color characteristic of another entity.
-
C.
primaryWavelength
Indicates the main or dominant wavelength associated with an entity, such as the principal wavelength at which it emits, reflects, or operates.
-
D.
primaryTextUsed
Indicates that a particular text is the main or principal textual content used in relation to another entity or resource.
-
E.
primaryAppearance
Indicates that the referenced entity is the main or most prominent visual or representational form in which another entity is typically depicted or recognized.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a25ab88190a72db43043c1f6ff |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410a001788190a457e41f53aaf90c |
completed | May 1, 2026, 2:32 a.m. |
Created at: April 18, 2026, 4:04 a.m.