Triple
T8114365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gdynia Orłowo Beach |
E189434
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Orłowo Pier |
E78629
|
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: Orłowo Pier | Statement: [Gdynia Orłowo Beach, near, Orłowo Pier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orłowo Pier Context triple: [Gdynia Orłowo Beach, near, Orłowo Pier]
-
A.
Orłowo
chosen
Orłowo is a coastal district of Gdynia in northern Poland, known for its scenic cliffs, pier, and Baltic Sea beaches.
-
B.
Orzysz
Orzysz is a small town in northeastern Poland known for its lakeside setting and proximity to extensive forests and military training grounds.
-
C.
Wejherowo
Wejherowo is a historic town in northern Poland known for its baroque Calvary complex and role as a local cultural and administrative center.
-
D.
Mrągowo
Mrągowo is a picturesque town in northeastern Poland known for its lakeside setting and popular summer cultural and music festivals.
-
E.
Oleśnica
Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
- 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_69ca82baad008190ab2859712b9b1607 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb432f2a24819097be6ab9b03567bd |
completed | March 31, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc943bdaa48190971bf57ae4fb5c21 |
completed | April 1, 2026, 3:42 a.m. |
Created at: March 30, 2026, 5:32 p.m.