Triple
T4144327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Lithuania |
E89346
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Marijampolė |
E443213
|
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: Marijampolė | Statement: [Central Lithuania, hasMajorCity, Marijampolė]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marijampolė Context triple: [Central Lithuania, hasMajorCity, Marijampolė]
-
A.
Marijampolė
chosen
Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
-
B.
Trakai
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.
-
C.
Alytus
Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
-
D.
Vilkaviškis
Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
-
E.
Švenčionys
Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af025d2984819095f299327cc399d5 |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b66b25d00481909eaf22c7c797c3f1 |
completed | March 15, 2026, 8:17 a.m. |
Created at: March 9, 2026, 3:43 p.m.