Triple
T12034069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imereti |
E286488
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Samtredia |
E91945
|
NE 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: Samtredia | Statement: [Imereti, containsCity, Samtredia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samtredia Context triple: [Imereti, containsCity, Samtredia]
-
A.
Samtredia
chosen
Samtredia is a town in western Georgia that serves as an important regional transportation hub, particularly for rail and road connections.
-
B.
Trysilelva
Trysilelva is a major river in eastern Norway that flows southward through the Trysil region and continues into Sweden as part of the Klarälven–Göta älv watercourse.
-
C.
Hemsila
Hemsila is a river in the Norwegian municipality of Hemsedal, known for its scenic valley course and popular trout fishing.
-
D.
Sätra
Sätra is a suburban district in southwestern Stockholm, Sweden, known for its residential areas and proximity to Lake Mälaren.
-
E.
Seskarö
Seskarö is a Swedish island in the northern Baltic Sea known for its forests, beaches, and traditional fishing and forestry communities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d6ec4b8819093ff50254a851444 |
completed | May 1, 2026, 12:32 p.m. |
Created at: April 8, 2026, 9:47 p.m.