Triple
T27623606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gagra |
E696142
|
entity |
| Predicate | wasPopularResortIn |
P158315
|
FINISHED |
| Object | Soviet Union |
—
|
NE NERFINISHED |
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: Soviet Union | Statement: [Gagra, wasPopularResortIn, Soviet Union]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasPopularResortIn Context triple: [Gagra, wasPopularResortIn, Soviet Union]
-
A.
hasPopularResort
Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
-
B.
wasSpaTown
Indicates that a place historically functioned as a spa town, known for its therapeutic baths or mineral springs.
-
C.
isPopularTouristDestinationIn
chosen
Indicates that a place is widely visited and favored by tourists within a specified geographic area or region.
-
D.
resort
Indicates that one entity is used or turned to as a final or alternative option by another entity, often after other possibilities have been exhausted.
-
E.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
- 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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f630df75248190a445f3c76dd5056f |
completed | May 2, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 2:16 p.m.