Triple
T129353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fürth |
E2619
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
|
E14681
|
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: FÜ | Statement: [Fürth, vehicleRegistrationCode, FÜ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FÜ Context triple: [Fürth, vehicleRegistrationCode, FÜ]
-
A.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
-
B.
FED
FED is the commonly used abbreviation for the Fluids Engineering Division, a professional group focused on research and advancements in fluid mechanics and related technologies.
-
C.
FRS
FRS is the post-nominal title used by Fellows of the Royal Society, denoting distinguished scientists elected to the United Kingdom’s national academy of sciences.
-
D.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
E.
SF
SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
- 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: FÜ Triple: [Fürth, vehicleRegistrationCode, FÜ]
Generated description
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FÜ Target entity description: FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
-
A.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
-
B.
FED
FED is the commonly used abbreviation for the Fluids Engineering Division, a professional group focused on research and advancements in fluid mechanics and related technologies.
-
C.
FRS
FRS is the post-nominal title used by Fellows of the Royal Society, denoting distinguished scientists elected to the United Kingdom’s national academy of sciences.
-
D.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
E.
SF
SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2576518e0819096b35d8af7a4d1bd |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2a3d5c7bc8190ba8b36db41a1a57f |
completed | Feb. 28, 2026, 8:14 a.m. |
| NEDg | Description generation | batch_69a2a4f0e7c081908966789fd07e59a2 |
completed | Feb. 28, 2026, 8:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2a58757d081908c7c5469c485f1cc |
completed | Feb. 28, 2026, 8:21 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.