Triple
T21730083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vortex |
E536381
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object |
KMG
KMG is a Dutch amusement ride manufacturer known for designing and producing portable and permanent thrill rides for fairs and theme parks worldwide.
|
E1500254
|
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: KMG | Statement: [Vortex, manufacturer, KMG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KMG Context triple: [Vortex, manufacturer, KMG]
-
A.
KMG
KMG is the IATA airport code for Kunming Changshui International Airport, a major air transport hub serving Kunming in Yunnan Province, China.
-
B.
KMG
KMG was the stock ticker symbol for Kerr-McGee Oil Industries, a former American energy company involved in oil and gas exploration and production.
-
C.
KGM
KGM is the three-letter National Rail station code assigned to Kingham railway station in Oxfordshire, England.
-
D.
KGM
KGM is the Turkish General Directorate of Highways, the national authority responsible for planning, constructing, and maintaining Turkey’s road network.
-
E.
KMKG
KMKG is the ICAO airport code for Muskegon County Airport in Muskegon, Michigan, United States.
- 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: KMG Triple: [Vortex, manufacturer, KMG]
Generated description
KMG is a Dutch amusement ride manufacturer known for designing and producing portable and permanent thrill rides for fairs and theme parks worldwide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KMG Target entity description: KMG is a Dutch amusement ride manufacturer known for designing and producing portable and permanent thrill rides for fairs and theme parks worldwide.
-
A.
KMG
KMG is the IATA airport code for Kunming Changshui International Airport, a major air transport hub serving Kunming in Yunnan Province, China.
-
B.
KMG
KMG was the stock ticker symbol for Kerr-McGee Oil Industries, a former American energy company involved in oil and gas exploration and production.
-
C.
KGM
KGM is the three-letter National Rail station code assigned to Kingham railway station in Oxfordshire, England.
-
D.
KGM
KGM is the Turkish General Directorate of Highways, the national authority responsible for planning, constructing, and maintaining Turkey’s road network.
-
E.
KMKG
KMKG is the ICAO airport code for Muskegon County Airport in Muskegon, Michigan, United States.
- 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd064fcc819084852b4248f65a81 |
completed | April 28, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a2ece628c8190b189516764b2ecdb |
completed | May 17, 2026, 9:10 p.m. |
| NEDg | Description generation | batch_6a0a32fb6c2c81908ecdcf3acad3cf36 |
completed | May 17, 2026, 9:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a33b435e08190a595c32a3747d1fd |
completed | May 17, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:48 p.m.