Triple
T17242869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marijampolė County |
E418545
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Lazdijai |
—
|
NE NERFINISHED |
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: Lazdijai | Statement: [Marijampolė County, containsTown, Lazdijai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lazdijai Context triple: [Marijampolė County, containsTown, Lazdijai]
-
A.
Lazdijai
chosen
Lazdijai is a small town in southern Lithuania, near the border with Poland, known as a local administrative and cultural center within the Dzūkija ethnographic region.
-
B.
Vilkaviškis
Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
-
C.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
-
D.
Zarasai
Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
-
E.
Alytus
Alytus is a city in southern Lithuania known as a regional cultural and economic center on the banks of the Nemunas River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e21003c81908c884a3c8712676a |
completed | April 19, 2026, 1:21 a.m. |
Created at: April 10, 2026, 5:39 a.m.