Triple
T15795461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | კონსტანტინე გამსახურდია |
E382965
|
entity |
| Predicate | დაბადებისადგილი |
P1
|
FINISHED |
| Object | აბაშა |
E102469
|
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: აბაშა | Statement: [კონსტანტინე გამსახურდია, დაბადებისადგილი, აბაშა]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: აბაშა Context triple: [კონსტანტინე გამსახურდია, დაბადებისადგილი, აბაშა]
-
A.
Abasár
Abasár is a village in northern Hungary known for its wine production and location near the Mátra Mountains.
-
B.
Asbarez
Asbarez is a long-running Armenian-American newspaper that serves as a key news source and voice for the Armenian diaspora, particularly in the United States.
-
C.
Abastumani
Abastumani is a small resort town in southern Georgia, historically known for its mountain climate and therapeutic sanatoriums.
-
D.
Abaza
Abaza is a Northwest Caucasian language spoken primarily in the Russian Republic of Karachay-Cherkessia, known for its complex consonant system and rich verbal morphology.
-
E.
Abasha
chosen
Abasha is a small town in western Georgia’s Samegrelo region, known as a local administrative and cultural center.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e0e1cc8190851b30b03cf9c9b8 |
completed | April 16, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90aea81c8190ad8bc0cdedf4b77a |
completed | May 9, 2026, 7:53 p.m. |
Created at: April 10, 2026, 4:48 a.m.