Triple
T13869313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deinze |
E333407
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Brzeg Dolny |
E317115
|
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: Brzeg Dolny | Statement: [Deinze, hasTwinTown, Brzeg Dolny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brzeg Dolny Context triple: [Deinze, hasTwinTown, Brzeg Dolny]
-
A.
Brzeg Dolny
chosen
Brzeg Dolny is a small industrial town in southwestern Poland, located on the Oder River in the Lower Silesian Voivodeship.
-
B.
Byczyna
Byczyna is a historic small town in southwestern Poland known for its well-preserved medieval urban layout and defensive walls.
-
C.
Brzeg
Brzeg is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
-
D.
Skawina
Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
-
E.
Czerwińsk nad Wisłą
Czerwińsk nad Wisłą is a historic village in east-central Poland, known for its medieval monastery and picturesque location on the Vistula River.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c530148190b11704300bbd5f9b |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdef1e4608190a137f340e06d5ddb |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:14 p.m.