Triple
T2845136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reichsgau Wartheland |
E62564
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Zduńska Wola
Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
|
E494875
|
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: Zduńska Wola | Statement: [Reichsgau Wartheland, containsCity, Zduńska Wola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zduńska Wola Context triple: [Reichsgau Wartheland, containsCity, Zduńska Wola]
-
A.
Jaworzno
Jaworzno is a city in southern Poland, located in the Silesian Voivodeship and known for its industrial heritage and role in the Upper Silesian urban area.
-
B.
Krotoszyn
Krotoszyn is a historic town in west-central Poland known for its medieval origins and changing political affiliations, including periods under Prussian and German rule.
-
C.
Parczew
Parczew is a small town in eastern Poland known for its historical roots and location within the Lublin region.
-
D.
Wadowice
Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
-
E.
Wyszogród
Wyszogród is a historic town in central Poland on the Vistula River, known for its medieval roots and strategic location that has seen numerous military events over the centuries.
- 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: Zduńska Wola Triple: [Reichsgau Wartheland, containsCity, Zduńska Wola]
Generated description
Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zduńska Wola Target entity description: Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
-
A.
Jaworzno
Jaworzno is a city in southern Poland, located in the Silesian Voivodeship and known for its industrial heritage and role in the Upper Silesian urban area.
-
B.
Krotoszyn
Krotoszyn is a historic town in west-central Poland known for its medieval origins and changing political affiliations, including periods under Prussian and German rule.
-
C.
Parczew
Parczew is a small town in eastern Poland known for its historical roots and location within the Lublin region.
-
D.
Wadowice
Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
-
E.
Wyszogród
Wyszogród is a historic town in central Poland on the Vistula River, known for its medieval roots and strategic location that has seen numerous military events over the centuries.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf1b58c88190b45d8c5a76dc52ac |
completed | March 7, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba392ad08190a66ccf58edecb722 |
completed | March 21, 2026, 3:33 p.m. |
| NEDg | Description generation | batch_69bebe2ca1cc8190bb7b5fb5b8fed9c7 |
completed | March 21, 2026, 3:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bebe8284d08190be8e991246662481 |
completed | March 21, 2026, 3:51 p.m. |
Created at: March 6, 2026, 10:02 p.m.