Triple
T8820905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GameController |
E209898
|
entity |
| Predicate | providesClass |
P32439
|
FINISHED |
| Object |
GCMouse
GCMouse is an Apple Game Controller framework class that represents and manages mouse input for games and apps on Apple platforms.
|
E759700
|
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: GCMouse | Statement: [GameController, providesClass, GCMouse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GCMouse Context triple: [GameController, providesClass, GCMouse]
-
A.
Mouse
"Mouse" is a short story featured in the speculative fiction collection "Smoke and Mirrors" by Neil Gaiman.
-
B.
GCM
GCM is the commonly used abbreviation for Grand Central Madison, a Long Island Rail Road terminal located beneath Grand Central Terminal in New York City.
-
C.
GCM
GCM (Galois/Counter Mode) is an authenticated encryption mode for block ciphers that provides both data confidentiality and integrity with high performance and parallelizability.
-
D.
GCI
GCI is the Getty Conservation Institute, a research and education organization dedicated to advancing the conservation of cultural heritage worldwide.
-
E.
mouse (vehicle of Ganesha)
The mouse, serving as the divine vehicle (vahana) of the Hindu god Ganesha, symbolizes humility, agility, and the ability to overcome obstacles.
- 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: GCMouse Triple: [GameController, providesClass, GCMouse]
Generated description
GCMouse is an Apple Game Controller framework class that represents and manages mouse input for games and apps on Apple platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GCMouse Target entity description: GCMouse is an Apple Game Controller framework class that represents and manages mouse input for games and apps on Apple platforms.
-
A.
Mouse
"Mouse" is a short story featured in the speculative fiction collection "Smoke and Mirrors" by Neil Gaiman.
-
B.
GCM
GCM is the commonly used abbreviation for Grand Central Madison, a Long Island Rail Road terminal located beneath Grand Central Terminal in New York City.
-
C.
GCM
GCM (Galois/Counter Mode) is an authenticated encryption mode for block ciphers that provides both data confidentiality and integrity with high performance and parallelizability.
-
D.
GCI
GCI is the Getty Conservation Institute, a research and education organization dedicated to advancing the conservation of cultural heritage worldwide.
-
E.
mouse (vehicle of Ganesha)
The mouse, serving as the divine vehicle (vahana) of the Hindu god Ganesha, symbolizes humility, agility, and the ability to overcome obstacles.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc601126248190b6f10c22f1aeac9a |
completed | April 1, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6fd064208190b1c8e1e1848763d2 |
completed | April 3, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69cf71e0bd14819089a9667d573f2295 |
completed | April 3, 2026, 7:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf743758c881909eecaf9bdbb047e5 |
completed | April 3, 2026, 8:03 a.m. |
Created at: March 30, 2026, 6:46 p.m.