Triple
T20509751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klaipėda County |
E503526
|
entity |
| Predicate | hasMajorResort |
P10436
|
FINISHED |
| Object | Palanga |
—
|
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: Palanga | Statement: [Klaipėda County, hasMajorResort, Palanga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palanga Context triple: [Klaipėda County, hasMajorResort, Palanga]
-
A.
Palanga
chosen
Palanga is a popular Lithuanian seaside resort town on the Baltic coast, known for its beaches, pier, and historic botanical park.
-
B.
Paldiski
Paldiski is a coastal town and former Soviet naval base in northwestern Estonia, located on the Pakri Peninsula by the Baltic Sea.
-
C.
Zarasai
Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
-
D.
Marijampolė
Marijampolė is a city in southern Lithuania that serves as an important regional center for administration, culture, and industry.
-
E.
Šilutė
Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcab8248190992e6ada23e5f253 |
completed | April 20, 2026, 9:42 p.m. |
Created at: April 16, 2026, 11:36 a.m.