Triple
T5620227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Szczecin-Goleniów Airport |
E147581
|
entity |
| Predicate | hasCityServed |
P3936
|
FINISHED |
| Object | Stargard |
E161104
|
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: Stargard | Statement: [Szczecin-Goleniów Airport, hasCityServed, Stargard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stargard Context triple: [Szczecin-Goleniów Airport, hasCityServed, Stargard]
-
A.
Stargard
chosen
Stargard is a town in northwestern Poland known for its medieval architecture and historical role as a strategic military and administrative center.
-
B.
Görlitz
Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
-
C.
Markranstädt
Markranstädt is a small town in the German state of Saxony, located near Leipzig and known for its local industry and proximity to the Kulkwitzer See recreation area.
-
D.
Bischofswerda
Bischofswerda is a small town in the Saxony region of eastern Germany, known as a local commercial and transport hub near the city of Dresden.
-
E.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
- 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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c022108db8819098739510366adee1 |
completed | March 22, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a0ed3748190875aacdf5e9ee211 |
completed | March 22, 2026, 9:07 p.m. |
Created at: March 22, 2026, 3:40 p.m.