Triple
T616879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quakenbrück |
E14423
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
OS
OS is the vehicle registration code for the German city of Osnabrück and its surrounding district.
|
E77449
|
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: OS | Statement: [Quakenbrück, hasVehicleRegistrationCode, OS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OS Context triple: [Quakenbrück, hasVehicleRegistrationCode, OS]
-
A.
Windows
Windows is a widely used family of graphical operating systems developed by Microsoft for personal computers, servers, and other devices.
-
B.
Windows NT
Windows NT is a family of Microsoft operating systems designed with a robust, secure, and modular architecture for professional and enterprise use.
-
C.
Solaris operating system
Solaris operating system is a Unix-based enterprise operating system known for its scalability, robustness, and advanced features such as ZFS, DTrace, and strong support for SPARC and x86 architectures.
-
D.
Linux
Linux is a widely used open-source Unix-like operating system kernel that powers servers, desktops, mobile devices, and embedded systems around the world.
-
E.
OSO
OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
- 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: OS Triple: [Quakenbrück, hasVehicleRegistrationCode, OS]
Generated description
OS is the vehicle registration code for the German city of Osnabrück and its surrounding district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OS Target entity description: OS is the vehicle registration code for the German city of Osnabrück and its surrounding district.
-
A.
Windows
Windows is a widely used family of graphical operating systems developed by Microsoft for personal computers, servers, and other devices.
-
B.
Windows NT
Windows NT is a family of Microsoft operating systems designed with a robust, secure, and modular architecture for professional and enterprise use.
-
C.
Solaris operating system
Solaris operating system is a Unix-based enterprise operating system known for its scalability, robustness, and advanced features such as ZFS, DTrace, and strong support for SPARC and x86 architectures.
-
D.
Linux
Linux is a widely used open-source Unix-like operating system kernel that powers servers, desktops, mobile devices, and embedded systems around the world.
-
E.
OSO
OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e22f3688190a512bec3f0347814 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a77b6648190a2d07471442b401a |
completed | March 2, 2026, 9:37 a.m. |
| NEDg | Description generation | batch_69a55b80320c8190a4e9eba92cd2839a |
completed | March 2, 2026, 9:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a55bcfce508190b58e0289775125f9 |
completed | March 2, 2026, 9:43 a.m. |
Created at: March 1, 2026, 7:35 p.m.