Triple
T6017406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Końskie County |
E133980
|
entity |
| Predicate | hasUrbanCentre |
P11388
|
FINISHED |
| Object | Końskie |
E194017
|
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: Końskie | Statement: [Końskie County, hasUrbanCentre, Końskie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Końskie Context triple: [Końskie County, hasUrbanCentre, Końskie]
-
A.
Końskie
chosen
Końskie is a town in south-central Poland known historically as a local industrial and administrative center.
-
B.
Sokołówka
Sokołówka is a small river in Poland known for flowing through the city of Łódź and its surrounding areas.
-
C.
Płośnica
Płośnica is a village in northern Poland located in the Warmian-Masurian Voivodeship, known for its rural character and proximity to the region’s lakes and forests.
-
D.
Korczyc
Korczyc is a Polish surname most notably borne by Władysław Korczyc, a general and political figure in mid-20th-century Poland.
-
E.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f8458588190a78aa32cbdbecfb1 |
completed | March 22, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11ce452748190b8b798a5cc2922f2 |
completed | March 23, 2026, 10:58 a.m. |
Created at: March 22, 2026, 4:07 p.m.