Triple
T1654755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saalekreis |
E35772
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
MQ
MQ is a German vehicle registration code assigned to the Saalekreis district in the state of Saxony-Anhalt.
|
E186994
|
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: MQ | Statement: [Saalekreis, vehicleRegistrationCode, MQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MQ Context triple: [Saalekreis, vehicleRegistrationCode, MQ]
-
A.
JMS
JMS (Java Message Service) is a Java API specification that enables applications to create, send, receive, and read messages in a loosely coupled, asynchronous, and reliable messaging system.
-
B.
Mailer
Mailer is a surname most notably associated with American novelist, journalist, and essayist Norman Mailer.
-
C.
Messenger
Messenger is Meta's cross-platform messaging application that enables users to send text, voice, and video communications across mobile and web.
-
D.
MSG
MSG refers to U.S. Marine Security Guards, specialized Marine Corps personnel assigned to protect American embassies, consulates, and other diplomatic facilities worldwide.
-
E.
MSG
MSG is a famous multi-purpose indoor arena in New York City known for hosting major sports events, concerts, and entertainment spectacles.
- 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: MQ Triple: [Saalekreis, vehicleRegistrationCode, MQ]
Generated description
MQ is a German vehicle registration code assigned to the Saalekreis district in the state of Saxony-Anhalt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MQ Target entity description: MQ is a German vehicle registration code assigned to the Saalekreis district in the state of Saxony-Anhalt.
-
A.
MSMQ
MSMQ (Microsoft Message Queuing) is a Microsoft messaging technology that enables reliable, asynchronous communication between distributed applications by queuing messages.
-
B.
JMS
JMS (Java Message Service) is a Java API specification that enables applications to create, send, receive, and read messages in a loosely coupled, asynchronous, and reliable messaging system.
-
C.
Mailer
Mailer is a surname most notably associated with American novelist, journalist, and essayist Norman Mailer.
-
D.
Messenger
Messenger is Meta's cross-platform messaging application that enables users to send text, voice, and video communications across mobile and web.
-
E.
MSG
MSG is a famous multi-purpose indoor arena in New York City known for hosting major sports events, concerts, and entertainment spectacles.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a8b597c81908a62b41718d85df6 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad60ad3bb48190a096ff7813748168 |
completed | March 8, 2026, 11:42 a.m. |
| NEDg | Description generation | batch_69ad61ff65b881909009c230780a146e |
completed | March 8, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad62ec3a80819085fef1c378b9abdc |
completed | March 8, 2026, 11:52 a.m. |
Created at: March 4, 2026, 7:29 p.m.