Triple
T17309119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leutenberg |
E420243
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
SOK
SOK is the vehicle registration code for the Saale-Orla-Kreis district in the German state of Thuringia.
|
E1261920
|
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: SOK | Statement: [Leutenberg, vehicleRegistrationCode, SOK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SOK Context triple: [Leutenberg, vehicleRegistrationCode, SOK]
-
A.
SOK
SOK is the abbreviation for the Swedish Olympic Committee, the organization responsible for overseeing Sweden's participation in the Olympic Games.
-
B.
SOK
SOK is the National Rail station code for South Kenton railway station in northwest London.
-
C.
SOKOM
SOKOM is the Danish Special Operations Command, the unified headquarters responsible for overseeing Denmark’s elite special operations forces.
-
D.
SOKO
SOKO was a Yugoslav aircraft manufacturer known for producing military and training aircraft, including the Soko J-22 Orao attack jet.
-
E.
SOCKOR
SOCKOR is the United States military’s theater special operations command responsible for overseeing and coordinating special operations activities on the Korean Peninsula.
- 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: SOK Triple: [Leutenberg, vehicleRegistrationCode, SOK]
Generated description
SOK is the vehicle registration code for the Saale-Orla-Kreis district in the German state of Thuringia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SOK Target entity description: SOK is the vehicle registration code for the Saale-Orla-Kreis district in the German state of Thuringia.
-
A.
SOK
SOK is the abbreviation for the Swedish Olympic Committee, the organization responsible for overseeing Sweden's participation in the Olympic Games.
-
B.
SOK
SOK is the National Rail station code for South Kenton railway station in northwest London.
-
C.
SOKOM
SOKOM is the Danish Special Operations Command, the unified headquarters responsible for overseeing Denmark’s elite special operations forces.
-
D.
SOKO
SOKO was a Yugoslav aircraft manufacturer known for producing military and training aircraft, including the Soko J-22 Orao attack jet.
-
E.
SOCKOR
SOCKOR is the United States military’s theater special operations command responsible for overseeing and coordinating special operations activities on the Korean Peninsula.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e439970cf08190bc9e49ba830da0d9 |
completed | April 19, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180e30934819087b7c838c8874aff |
completed | May 11, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_6a0185a7e5188190a15d835019fc226f |
completed | May 11, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0186504460819097f80978b03c7296 |
completed | May 11, 2026, 7:33 a.m. |
Created at: April 10, 2026, 5:43 a.m.