Triple
T1156396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trzebinia |
E23791
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Chrzanów |
E24617
|
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: Chrzanów | Statement: [Trzebinia, hasNearbyCity, Chrzanów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chrzanów Context triple: [Trzebinia, hasNearbyCity, Chrzanów]
-
A.
Chrzanów
chosen
Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
-
B.
Ojców
Ojców is a small village in southern Poland known as a gateway to the picturesque Ojców National Park in the Kraków-Częstochowa Upland.
-
C.
Glogów
Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
-
D.
Starachowice
Starachowice is an industrial town in south-central Poland known for its automotive and metalworking industries and its location near the Świętokrzyskie (Holy Cross) Mountains.
-
E.
Chorzów
Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc92ae008190a587c12ecc9a502a |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7190fb84819095e6ebf2eeb50148 |
completed | March 9, 2026, 7:06 a.m. |
Created at: March 1, 2026, 7:44 p.m.