Triple
T12034077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imereti |
E286488
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Kobuleti |
E109179
|
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: Kobuleti | Statement: [Imereti, containsCity, Kobuleti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kobuleti Context triple: [Imereti, containsCity, Kobuleti]
-
A.
Kobuleti
chosen
Kobuleti is a Georgian Black Sea resort town known for its long pebble beaches and role as a popular holiday destination in the autonomous region of Adjara.
-
B.
Kardenakhi
Kardenakhi is a Georgian village in the Kakheti region renowned for producing high-quality wines under its own appellation.
-
C.
Goubuli
Goubuli is a famous Chinese food brand best known for its traditional Tianjin-style stuffed buns (baozi) with a long history and strong cultural recognition.
-
D.
Balka
Balka is a coastal village and beach area on the Danish island of Bornholm, known for its shallow, child-friendly sandy shoreline and holiday atmosphere.
-
E.
Gevaş
Gevaş is a town and district in eastern Turkey, situated on the southern shore of Lake Van in Van Province.
- 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.