Triple
T11111616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mokotów |
E262769
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Wyględów
Wyględów is a neighborhood within the Mokotów district of Warsaw, Poland, known for its residential character and proximity to key transport routes and green areas.
|
E905822
|
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: Wyględów | Statement: [Mokotów, contains, Wyględów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wyględów Context triple: [Mokotów, contains, Wyględów]
-
A.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
B.
Goleniów
Goleniów is a town in northwestern Poland that serves as a local transport hub and gateway to the nearby regional capital Szczecin.
-
C.
Łęczna
Łęczna is a town in eastern Poland known for its location near the Lublin Coal Basin and as a local administrative and service center.
-
D.
Tarnowskie Góry
Tarnowskie Góry is a historic town in southern Poland renowned for its UNESCO-listed silver, lead, and zinc mining heritage.
-
E.
Szczawnica
Szczawnica is a Polish spa and tourist town in southern Lesser Poland, known for its mineral springs, health resorts, and scenic location in the Pieniny region near the Dunajec River.
- 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: Wyględów Triple: [Mokotów, contains, Wyględów]
Generated description
Wyględów is a neighborhood within the Mokotów district of Warsaw, Poland, known for its residential character and proximity to key transport routes and green areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wyględów Target entity description: Wyględów is a neighborhood within the Mokotów district of Warsaw, Poland, known for its residential character and proximity to key transport routes and green areas.
-
A.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
B.
Goleniów
Goleniów is a town in northwestern Poland that serves as a local transport hub and gateway to the nearby regional capital Szczecin.
-
C.
Łęczna
Łęczna is a town in eastern Poland known for its location near the Lublin Coal Basin and as a local administrative and service center.
-
D.
Tarnowskie Góry
Tarnowskie Góry is a historic town in southern Poland renowned for its UNESCO-listed silver, lead, and zinc mining heritage.
-
E.
Szczawnica
Szczawnica is a Polish spa and tourist town in southern Lesser Poland, known for its mineral springs, health resorts, and scenic location in the Pieniny region near the Dunajec River.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa42ec4819085a2e802e00d9f02 |
completed | April 9, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d759bc88190b670c373f3647a41 |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e4307baca48190bbf82f8235d7e2c7 |
completed | April 19, 2026, 1:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e43771eaec8190be9bb709723931e0 |
completed | April 19, 2026, 2:01 a.m. |
Created at: April 8, 2026, 9:27 p.m.