Triple
T8532100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neunkirchen |
E201976
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Wolsztyn
Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
|
E914022
|
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: Wolsztyn | Statement: [Neunkirchen, twinTown, Wolsztyn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wolsztyn Context triple: [Neunkirchen, twinTown, Wolsztyn]
-
A.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
B.
Tychy
Tychy is a city in the Silesian region of southern Poland, known for its brewing industry and role as a planned industrial center.
-
C.
Kluczbork
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
-
D.
Olsztynek
Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
-
E.
Olsztyn
Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of 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: Wolsztyn Triple: [Neunkirchen, twinTown, Wolsztyn]
Generated description
Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wolsztyn Target entity description: Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
-
A.
Kalisz
Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
-
B.
Tychy
Tychy is a city in the Silesian region of southern Poland, known for its brewing industry and role as a planned industrial center.
-
C.
Kluczbork
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
-
D.
Olsztynek
Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
-
E.
Olsztyn
Olsztyn is a historic city in northern Poland known for its medieval architecture, lakes, and role as the capital of 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_69ca832355b08190b8b6a4ab4a4a3554 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe676e2ac8190b65a3d2a935776fd |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cbacad608190adddd91f13e4113b |
completed | April 19, 2026, 12:33 p.m. |
| NEDg | Description generation | batch_69e4d9e87508819080932fac06fb754d |
completed | April 19, 2026, 1:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4dda28b0081909245b65faae3533b |
completed | April 19, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:17 p.m.