Triple
T5432859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SpriteKit |
E121536
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object |
SKLabelNode
SKLabelNode is a SpriteKit class used to display and render text labels within 2D game scenes.
|
E518840
|
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: SKLabelNode | Statement: [SpriteKit, includes, SKLabelNode]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SKLabelNode Context triple: [SpriteKit, includes, SKLabelNode]
-
A.
KLAS
KLAS is the ICAO airport code for Harry Reid International Airport, the primary commercial airport serving Las Vegas, Nevada.
-
B.
SKN
SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
-
C.
K-TAG
K-TAG is an electronic toll collection system used on the Kansas Turnpike and compatible highways, allowing drivers to pay tolls automatically via a windshield-mounted transponder.
-
D.
SKU
SKU is the three-letter ICAO airline designator assigned to Sky Airline, used in aviation operations and air traffic control.
-
E.
KSL
KSL is the primary sign language used by the Deaf community in South Korea, with its own distinct grammar and vocabulary separate from spoken Korean.
- 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: SKLabelNode Triple: [SpriteKit, includes, SKLabelNode]
Generated description
SKLabelNode is a SpriteKit class used to display and render text labels within 2D game scenes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SKLabelNode Target entity description: SKLabelNode is a SpriteKit class used to display and render text labels within 2D game scenes.
-
A.
KLAS
KLAS is the ICAO airport code for Harry Reid International Airport, the primary commercial airport serving Las Vegas, Nevada.
-
B.
SKN
SKN is the station code for South Kensington tube station, a major London Underground interchange serving the South Kensington area.
-
C.
K-TAG
K-TAG is an electronic toll collection system used on the Kansas Turnpike and compatible highways, allowing drivers to pay tolls automatically via a windshield-mounted transponder.
-
D.
SKU
SKU is the three-letter ICAO airline designator assigned to Sky Airline, used in aviation operations and air traffic control.
-
E.
KSL
KSL is the primary sign language used by the Deaf community in South Korea, with its own distinct grammar and vocabulary separate from spoken Korean.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8840ade481909dae2eecc77d73b8 |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac985e48190ba9610e0563c73ab |
completed | March 22, 2026, 12:41 a.m. |
| NEDg | Description generation | batch_69bf3b663b148190807d35421c911d74 |
completed | March 22, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf3c2b9d04819081a946e9f68c4eb2 |
completed | March 22, 2026, 12:47 a.m. |
Created at: March 20, 2026, 2:06 p.m.