Triple
T236444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silesia |
E4833
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object |
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
|
E32146
|
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: Katowice | Statement: [Silesia, majorCity, Katowice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katowice Context triple: [Silesia, majorCity, Katowice]
-
A.
Wrocław
Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
-
B.
Cieszyn Silesia
Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
-
C.
Poznań
Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
-
D.
Kraków
Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
-
E.
Łódź
Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
- 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: Katowice Triple: [Silesia, majorCity, Katowice]
Generated description
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Katowice Target entity description: Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
A.
Wrocław
Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
-
B.
Cieszyn Silesia
Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
-
C.
Poznań
Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
-
D.
Kraków
Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
-
E.
Łódź
Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ccab7648190be6e4f5febc1e313 |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3736e4010819089000ed60dbf519c |
completed | Feb. 28, 2026, 10:59 p.m. |
| NEDg | Description generation | batch_69a373c9a698819088b3981ffbf85f9b |
completed | Feb. 28, 2026, 11:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3742d7efc81908a46e928326e43fa |
completed | Feb. 28, 2026, 11:03 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.