Triple
T1517174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katowice |
E32146
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Gliwice
Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
|
E333563
|
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: Gliwice | Statement: [Katowice, near, Gliwice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gliwice Context triple: [Katowice, near, Gliwice]
-
A.
Chorzów
Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
-
B.
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
C.
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.
-
D.
Wałbrzych
Wałbrzych is a city in southwestern Poland known for its industrial heritage, historic coal mining, and proximity to the Sudetes mountains.
-
E.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
- 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: Gliwice Triple: [Katowice, near, Gliwice]
Generated description
Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gliwice Target entity description: Gliwice is a historic industrial and academic city in southern Poland’s Silesian region, known for its engineering university and the landmark Gliwice Radio Tower.
-
A.
Chorzów
Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
-
B.
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
C.
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.
-
D.
Wałbrzych
Wałbrzych is a city in southwestern Poland known for its industrial heritage, historic coal mining, and proximity to the Sudetes mountains.
-
E.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907eb7d108190bf26199744d510d7 |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235106b1c8190ae6d4d02aefd69a9 |
completed | March 12, 2026, 3:37 a.m. |
| NEDg | Description generation | batch_69b23634df448190b63f08b107511cb2 |
completed | March 12, 2026, 3:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b236f6ca1c8190ad3ca4f329d1a5ae |
completed | March 12, 2026, 3:45 a.m. |
Created at: March 4, 2026, 7:26 p.m.