Triple
T2406850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LOT Polish Airlines |
E50294
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object |
LOT Charters
LOT Charters is a Polish charter airline brand operating leisure and charter flights as part of the LOT Polish Airlines group.
|
E262364
|
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: LOT Charters | Statement: [LOT Polish Airlines, hasSubsidiary, LOT Charters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LOT Charters Context triple: [LOT Polish Airlines, hasSubsidiary, LOT Charters]
-
A.
LOTS
LOTS is the stock ticker symbol for Lotus Development Corporation, a pioneering software company best known for its Lotus 1-2-3 spreadsheet application.
-
B.
Lotusmiles
Lotusmiles is the frequent-flyer loyalty program of Vietnam Airlines, offering members mileage accrual and tiered benefits for their travel with the carrier and its partners.
-
C.
Select Car Leasing Stadium
Select Car Leasing Stadium is a football stadium in Reading, England, best known as the home venue of Reading Football Club.
-
D.
Lot
Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
-
E.
Lot
Lot is a river in southwestern France known for flowing through scenic valleys and historic towns before joining the Garonne.
- 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: LOT Charters Triple: [LOT Polish Airlines, hasSubsidiary, LOT Charters]
Generated description
LOT Charters is a Polish charter airline brand operating leisure and charter flights as part of the LOT Polish Airlines group.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LOT Charters Target entity description: LOT Charters is a Polish charter airline brand operating leisure and charter flights as part of the LOT Polish Airlines group.
-
A.
LOTS
LOTS is the stock ticker symbol for Lotus Development Corporation, a pioneering software company best known for its Lotus 1-2-3 spreadsheet application.
-
B.
Lotusmiles
Lotusmiles is the frequent-flyer loyalty program of Vietnam Airlines, offering members mileage accrual and tiered benefits for their travel with the carrier and its partners.
-
C.
Select Car Leasing Stadium
Select Car Leasing Stadium is a football stadium in Reading, England, best known as the home venue of Reading Football Club.
-
D.
Lot
Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
-
E.
Lot
Lot is a river in southwestern France known for flowing through scenic valleys and historic towns before joining the Garonne.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8fcd3008190b27325e6829ae7ce |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3eba9d08190a2c63e590e08b4df |
completed | March 9, 2026, 11:50 a.m. |
| NEDg | Description generation | batch_69aeb4a5e9c481908426fe51343a1342 |
completed | March 9, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeb52bec1881909c589aea2af3684c |
completed | March 9, 2026, 11:55 a.m. |
Created at: March 4, 2026, 7:58 p.m.