Triple
T1907627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linux Mint |
E38037
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object |
mintDrivers
mintDrivers is a Linux Mint tool for managing and installing proprietary and open-source hardware drivers on the system.
|
E212340
|
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: mintDrivers | Statement: [Linux Mint, includes, mintDrivers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: mintDrivers Context triple: [Linux Mint, includes, mintDrivers]
-
A.
IM Motors
IM Motors is a Chinese premium electric vehicle brand known for its smart, tech-focused cars developed under SAIC Motor.
-
B.
Moto
Moto is a consumer electronics brand used by Motorola Mobility for its line of smartphones and related mobile devices.
-
C.
MyTeksi
MyTeksi is the original Malaysian taxi-booking app that later evolved into Grab, one of Southeast Asia’s leading ride-hailing and super-app platforms.
-
D.
Terminal 4S
Terminal 4S is the satellite terminal of Madrid’s Adolfo Suárez Madrid–Barajas Airport, primarily serving international and long-haul flights with modern, high-capacity facilities.
-
E.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
- 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: mintDrivers Triple: [Linux Mint, includes, mintDrivers]
Generated description
mintDrivers is a Linux Mint tool for managing and installing proprietary and open-source hardware drivers on the system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: mintDrivers Target entity description: mintDrivers is a Linux Mint tool for managing and installing proprietary and open-source hardware drivers on the system.
-
A.
IM Motors
IM Motors is a Chinese premium electric vehicle brand known for its smart, tech-focused cars developed under SAIC Motor.
-
B.
Moto
Moto is a consumer electronics brand used by Motorola Mobility for its line of smartphones and related mobile devices.
-
C.
MyTeksi
MyTeksi is the original Malaysian taxi-booking app that later evolved into Grab, one of Southeast Asia’s leading ride-hailing and super-app platforms.
-
D.
Terminal 4S
Terminal 4S is the satellite terminal of Madrid’s Adolfo Suárez Madrid–Barajas Airport, primarily serving international and long-haul flights with modern, high-capacity facilities.
-
E.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1b44174819084fa06faf1930221 |
completed | March 7, 2026, 5:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeafb063481908a08f5570acc5b57 |
completed | March 8, 2026, 9:32 p.m. |
| NEDg | Description generation | batch_69adec22c5e48190af85fa4a1d4c5d8d |
completed | March 8, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adec9a840c8190a03f4de0f03a0e10 |
completed | March 8, 2026, 9:39 p.m. |
Created at: March 4, 2026, 7:35 p.m.