Triple
T9189729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prabuty |
E220549
|
entity |
| Predicate | railwayLinesConnectTo |
P848
|
FINISHED |
| Object | Kwidzyn |
E281978
|
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: Kwidzyn | Statement: [Prabuty, railwayLinesConnectTo, Kwidzyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kwidzyn Context triple: [Prabuty, railwayLinesConnectTo, Kwidzyn]
-
A.
Kwidzyn
chosen
Kwidzyn is a historic town in northern Poland known for its medieval Teutonic castle complex and Gothic cathedral.
-
B.
Gryfice
Gryfice is a historic town in northwestern Poland known for its medieval urban layout and remnants of defensive walls.
-
C.
Świnoujście
Świnoujście is a Polish port city and seaside resort on the Baltic Sea, known for its wide beaches, spa facilities, and strategic location at the mouth of the Świna River.
-
D.
Kościerzyna
Kościerzyna is a historic town in northern Poland known as a local cultural and economic center within the Kashubian region.
-
E.
Giżycko
Giżycko is a popular lakeside town in northeastern Poland, known as a major sailing and tourism center in the Masurian Lake District.
- 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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd5bd8c5c81909d0cdbcd7410fcee |
completed | April 1, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de54a30b748190bb791078e9dde442 |
completed | April 14, 2026, 2:52 p.m. |
Created at: March 30, 2026, 7:24 p.m.