Triple
T6669527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PZL Warszawa-Okęcie |
E151689
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object |
Okęcie
Okęcie is a district in Warsaw, Poland, best known for hosting the city’s main international airport and various aviation-related facilities.
|
E610242
|
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: Okęcie | Statement: [PZL Warszawa-Okęcie, headquartersLocation, Okęcie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okęcie Context triple: [PZL Warszawa-Okęcie, headquartersLocation, Okęcie]
-
A.
Mokotów
Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
-
B.
Ujazdów
Ujazdów is a historic neighborhood in central Warsaw, known for its palaces, government buildings, and extensive green areas including parks and gardens.
-
C.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
D.
Maków Podhalański
Maków Podhalański is a small town in southern Poland, situated in the Lesser Poland Voivodeship and known as a local center in the mountainous Beskid region.
-
E.
Śródmieście
Śródmieście is the central downtown district of the Polish port city of Gdynia, known for its urban core, services, and seaside location.
- 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: Okęcie Triple: [PZL Warszawa-Okęcie, headquartersLocation, Okęcie]
Generated description
Okęcie is a district in Warsaw, Poland, best known for hosting the city’s main international airport and various aviation-related facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Okęcie Target entity description: Okęcie is a district in Warsaw, Poland, best known for hosting the city’s main international airport and various aviation-related facilities.
-
A.
Mokotów
Mokotów is a large, centrally located district of Warsaw known for its residential neighborhoods, parks, and business centers.
-
B.
Ujazdów
Ujazdów is a historic neighborhood in central Warsaw, known for its palaces, government buildings, and extensive green areas including parks and gardens.
-
C.
Łeba
Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
-
D.
Maków Podhalański
Maków Podhalański is a small town in southern Poland, situated in the Lesser Poland Voivodeship and known as a local center in the mountainous Beskid region.
-
E.
Śródmieście
Śródmieście is the central downtown district of the Polish port city of Gdynia, known for its urban core, services, and seaside location.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0c7d9148190b3fbb870851d917b |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef12fcfc819086b37dc9b9929663 |
completed | March 27, 2026, 8:56 p.m. |
| NEDg | Description generation | batch_69c6f0a498cc8190a0494082b91b012d |
completed | March 27, 2026, 9:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f136ac648190b94a7cda43139fd0 |
completed | March 27, 2026, 9:05 p.m. |
Created at: March 27, 2026, 2:02 p.m.