Triple
T11969971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubusz Voivodeship |
E284891
|
entity |
| Predicate | hasLargestCities |
P235
|
FINISHED |
| Object | Słubice |
E827145
|
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: Słubice | Statement: [Lubusz Voivodeship, hasLargestCities, Słubice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Słubice Context triple: [Lubusz Voivodeship, hasLargestCities, Słubice]
-
A.
Słubice
chosen
Słubice is a Polish border town on the Oder River, located directly across from Frankfurt (Oder) and historically part of the same urban area.
-
B.
Bolesławiec
Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
-
C.
Racibórz
Racibórz is a historic town in southern Poland, located in the Silesian region near the Czech border, known for its medieval heritage and industrial traditions.
-
D.
Sławno
Sławno is a small historic town in northwestern Poland known for its medieval urban layout and location near the Baltic coast.
-
E.
Kluczbork
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a4fffa7c81909bcc833b44ddf66f |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 8, 2026, 9:46 p.m.