Triple
T14229448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | topbonus |
E352712
|
entity |
| Predicate | formerOperator |
P179
|
FINISHED |
| Object |
NIKI
NIKI was an Austrian low-cost airline founded by former Formula 1 driver Niki Lauda that operated primarily European leisure and short-haul routes before ceasing operations.
|
E1088052
|
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: NIKI | Statement: [topbonus, formerOperator, NIKI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NIKI Context triple: [topbonus, formerOperator, NIKI]
-
A.
Niki
Niki is a small town in Hokkaido, Japan, known for its fruit farming and rural scenery.
-
B.
Niki
Niki is a given name that can be used for people of any gender in various cultures.
-
C.
NIK
NIK is the Polish acronym for the Supreme Audit Office, Poland’s highest independent state audit institution responsible for overseeing public finances and government operations.
-
D.
NIKL
NIKL is the abbreviated name of South Korea’s National Institute of Korean Language, the government body responsible for researching, standardizing, and promoting the Korean language.
-
E.
Nikki
Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
- 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: NIKI Triple: [topbonus, formerOperator, NIKI]
Generated description
NIKI was an Austrian low-cost airline founded by former Formula 1 driver Niki Lauda that operated primarily European leisure and short-haul routes before ceasing operations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NIKI Target entity description: NIKI was an Austrian low-cost airline founded by former Formula 1 driver Niki Lauda that operated primarily European leisure and short-haul routes before ceasing operations.
-
A.
Niki
Niki is a small town in Hokkaido, Japan, known for its fruit farming and rural scenery.
-
B.
Niki
Niki is a given name that can be used for people of any gender in various cultures.
-
C.
NIK
NIK is the Polish acronym for the Supreme Audit Office, Poland’s highest independent state audit institution responsible for overseeing public finances and government operations.
-
D.
NIKL
NIKL is the abbreviated name of South Korea’s National Institute of Korean Language, the government body responsible for researching, standardizing, and promoting the Korean language.
-
E.
Nikki
Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622b89fc8190af08dab9e1976759 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2819bfec8190b555632338c53740 |
completed | May 8, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69fd2c3388f0819085aa203ec88fe81e |
completed | May 8, 2026, 12:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2cc71b248190aa78697c5bc397e6 |
completed | May 8, 2026, 12:22 a.m. |
Created at: April 10, 2026, 1:07 a.m.