Triple
T5601026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simmern |
E147118
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
SIM
SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
|
E533676
|
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: SIM | Statement: [Simmern, vehicleRegistrationCode, SIM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SIM Context triple: [Simmern, vehicleRegistrationCode, SIM]
-
A.
SIM
SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
-
B.
IMS
IMS is IBM's hierarchical database and transaction management system widely used on mainframe platforms for high-volume, mission-critical applications.
-
C.
IMS
IMS is the NATO International Military Staff, the body that provides strategic military advice and support to NATO’s decision-making structures.
-
D.
IMS
IMS is the IEEE MTT-S International Microwave Symposium, a leading annual conference and exhibition focused on microwave theory, techniques, and technologies.
-
E.
IMS
IMS (IP Multimedia Subsystem) is a standardized architectural framework for delivering IP-based multimedia services over mobile and fixed networks.
- 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: SIM Triple: [Simmern, vehicleRegistrationCode, SIM]
Generated description
SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SIM Target entity description: SIM is the vehicle registration code used on license plates for vehicles registered in the Simmern region of Germany.
-
A.
SIM
SIM is the commonly used abbreviation for the Science and Industry Museum in Manchester, a major UK museum dedicated to the history and impact of science, technology, and industry.
-
B.
IMS
IMS is IBM's hierarchical database and transaction management system widely used on mainframe platforms for high-volume, mission-critical applications.
-
C.
IMS
IMS is the NATO International Military Staff, the body that provides strategic military advice and support to NATO’s decision-making structures.
-
D.
IMS
IMS is the IEEE MTT-S International Microwave Symposium, a leading annual conference and exhibition focused on microwave theory, techniques, and technologies.
-
E.
IMS
IMS (IP Multimedia Subsystem) is a standardized architectural framework for delivering IP-based multimedia services over mobile and fixed networks.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020da519c81908626b243e40db263 |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02873b1dc8190b11a6c069f3e4f7e |
completed | March 22, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69c035f54f6c8190badbfd800012c399 |
completed | March 22, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c036f0edb48190bfa74f7f2c9d9ab1 |
completed | March 22, 2026, 6:37 p.m. |
Created at: March 22, 2026, 3:39 p.m.