Triple
T13084006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noteć |
E310281
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Czarnków |
E1175734
|
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: Czarnków | Statement: [Noteć, passesNear, Czarnków]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Czarnków Context triple: [Noteć, passesNear, Czarnków]
-
A.
Czarnków
chosen
Czarnków is a historic town in western Poland’s Greater Poland Voivodeship, known for its picturesque setting on the Noteć River and regional brewing traditions.
-
B.
Skrzyczne
Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
-
C.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
D.
Czersk
Czersk is a town in northern Poland known for its location in the Pomeranian Voivodeship and its historical ties to regional noble lineages.
-
E.
Chrzanów
Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981361e8c819099376435aa3a7aa3 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfb725d48190bdca0a85ca7f440c |
completed | May 10, 2026, 6:34 p.m. |
Created at: April 9, 2026, 9:02 p.m.