Triple
T14225459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Praga |
E352605
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Saska Kępa
Saska Kępa is a leafy, upscale residential neighborhood in Warsaw known for its modernist villas, cosmopolitan atmosphere, and vibrant café and restaurant scene.
|
E1087238
|
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: Saska Kępa | Statement: [Praga, hasPart, Saska Kępa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saska Kępa Context triple: [Praga, hasPart, Saska Kępa]
-
A.
Kornat
Kornat is the largest and most prominent island in Croatia’s Kornati archipelago, known for its rugged coastline and inclusion within Kornati National Park.
-
B.
Białołęka
Białołęka is a rapidly developing residential district in the northeastern part of Warsaw, known for its modern housing estates and expanding infrastructure.
-
C.
Skawica
Skawica is a village in southern Poland, located in the Lesser Poland Voivodeship within the administrative district of powiat suski.
-
D.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
E.
Kopaska
Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
- 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: Saska Kępa Triple: [Praga, hasPart, Saska Kępa]
Generated description
Saska Kępa is a leafy, upscale residential neighborhood in Warsaw known for its modernist villas, cosmopolitan atmosphere, and vibrant café and restaurant scene.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saska Kępa Target entity description: Saska Kępa is a leafy, upscale residential neighborhood in Warsaw known for its modernist villas, cosmopolitan atmosphere, and vibrant café and restaurant scene.
-
A.
Kornat
Kornat is the largest and most prominent island in Croatia’s Kornati archipelago, known for its rugged coastline and inclusion within Kornati National Park.
-
B.
Białołęka
Białołęka is a rapidly developing residential district in the northeastern part of Warsaw, known for its modern housing estates and expanding infrastructure.
-
C.
Skawica
Skawica is a village in southern Poland, located in the Lesser Poland Voivodeship within the administrative district of powiat suski.
-
D.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
E.
Kopaska
Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6228e53c8190abbe4e2d88a7362a |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd281611b48190b787e38ba9c733a4 |
completed | May 8, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69fd2a5c80308190868967a402c5fa42 |
completed | May 8, 2026, 12:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2af4ddf8819089435b849415b941 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 10, 2026, 1:06 a.m.