Triple
T20601840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Humanities, Klaipėda University |
E506200
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Klaipėda |
—
|
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: Klaipėda | Statement: [Department of Humanities, Klaipėda University, locatedIn, Klaipėda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klaipėda Context triple: [Department of Humanities, Klaipėda University, locatedIn, Klaipėda]
-
A.
Klaipėda
chosen
Klaipėda is a Lithuanian port city on the Baltic Sea known as the country’s main maritime gateway and a key regional transport and industrial hub.
-
B.
Kaunas
Kaunas is the second-largest city in Lithuania, known as a historic cultural and academic center located at the confluence of the Nemunas and Neris rivers.
-
C.
Tauragė
Tauragė is a town in western Lithuania known as an administrative, cultural, and economic center of the surrounding region.
-
D.
Zarasai
Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
-
E.
Radviliškis
Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa20f5c881909265ce7d96efc487 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:41 a.m.