Triple
T1945077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warmia-Masuria region |
E42042
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Korsze
Korsze is a small town in northern Poland, situated in the Warmian-Masurian Voivodeship and known as a local rail and service center for the surrounding rural area.
|
E224195
|
NE FINISHED |
How this triple was built (4 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: Korsze | Statement: [Warmia-Masuria region, hasMajorCity, Korsze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korsze Context triple: [Warmia-Masuria region, hasMajorCity, Korsze]
-
A.
Orzysz
Orzysz is a small town in northeastern Poland known for its lakeside setting and proximity to extensive forests and military training grounds.
-
B.
Końskie
Końskie is a town in south-central Poland known historically as a local industrial and administrative center.
-
C.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
D.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
E.
Pasłęk
Pasłęk is a historic town in northern Poland known for its medieval architecture and location within the Warmian-Masurian Voivodeship.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Korsze Triple: [Warmia-Masuria region, hasMajorCity, Korsze]
Generated description
Korsze is a small town in northern Poland, situated in the Warmian-Masurian Voivodeship and known as a local rail and service center for the surrounding rural area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Korsze Target entity description: Korsze is a small town in northern Poland, situated in the Warmian-Masurian Voivodeship and known as a local rail and service center for the surrounding rural area.
-
A.
Orzysz
Orzysz is a small town in northeastern Poland known for its lakeside setting and proximity to extensive forests and military training grounds.
-
B.
Końskie
Końskie is a town in south-central Poland known historically as a local industrial and administrative center.
-
C.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
D.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
E.
Pasłęk
Pasłęk is a historic town in northern Poland known for its medieval architecture and location within the Warmian-Masurian Voivodeship.
- F. None of above. chosen
Provenance (5 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb300af2481908ae359972843c1ef |
completed | March 7, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ac7cd1881908d9284370de529ce |
completed | March 8, 2026, 11:48 p.m. |
| NEDg | Description generation | batch_69ae0b30cc688190ba8f437e683a319d |
completed | March 8, 2026, 11:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0b9e7c64819093461c74b98e48ca |
completed | March 8, 2026, 11:51 p.m. |
Created at: March 4, 2026, 7:36 p.m.