Triple
T10127212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karaims |
E226244
|
entity |
| Predicate | historicalLanguageVariety |
P6149
|
FINISHED |
| Object | Trakai Karaim |
E286925
|
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: Trakai Karaim | Statement: [Karaims, historicalLanguageVariety, Trakai Karaim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trakai Karaim Context triple: [Karaims, historicalLanguageVariety, Trakai Karaim]
-
A.
Trakai
chosen
Trakai is a historic Lithuanian town famed for its medieval island castle and former status as a political center of the Grand Duchy of Lithuania.
-
B.
Kovno
Kovno is the historical name for Kaunas, a major city in Lithuania that was once part of the Russian Empire and had a significant Jewish community.
-
C.
Sakiai
Sakiai is a small town in southwestern Lithuania known for its proximity to the Russian and Polish borders and its role as a local administrative and cultural center.
-
D.
Mozyr
Mozyr is a city in southern Belarus known as an important regional industrial and cultural center on the Pripyat River.
-
E.
Druskininkai
Druskininkai is a well-known spa and resort town in southern Lithuania, famous for its mineral springs and wellness tourism.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2eef7388190b95ffd02814f2d1f |
completed | April 2, 2026, 2:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e5c29f6c8190b347a6963ca46dac |
completed | April 5, 2026, 10:44 p.m. |
Created at: March 30, 2026, 9:05 p.m.