Triple
T30928889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tartumaa |
E787934
|
entity |
| Predicate | hasTraditionalRegionType |
P197770
|
FINISHED |
| Object | county |
—
|
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: county | Statement: [Tartumaa, hasTraditionalRegionType, county]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalRegionType Context triple: [Tartumaa, hasTraditionalRegionType, county]
-
A.
hasTraditionalTerritoryType
Indicates that an entity’s traditional territory is classified as belonging to a specific type or category of territory.
-
B.
hasTraditionalRegionCharacter
Indicates that an entity possesses a characteristic or feature that is typical of, or traditionally associated with, a specific region.
-
C.
hasTraditionalLanguageRegion
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
D.
hasHistoricalRegionType
Indicates that a historical region is associated with a specific type or classification of historical region.
-
E.
hasTraditionalArea
Indicates that an entity is associated with or belongs to a customary or historically recognized geographic area.
- 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
| PDg | Predicate description generation | batch_69feaa477f7c81909382b3aa77e7e11c |
completed | May 9, 2026, 3:30 a.m. |
Created at: April 29, 2026, 8:52 p.m.