Triple
T11272754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadtmitte (Bad Honnef) |
E266853
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
SU
SU is the vehicle registration code for the Rhein-Sieg-Kreis district in the German state of North Rhine-Westphalia.
|
E916217
|
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: SU | Statement: [Stadtmitte (Bad Honnef), vehicleRegistrationCode, SU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SU Context triple: [Stadtmitte (Bad Honnef), vehicleRegistrationCode, SU]
-
A.
SU
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
-
B.
SU
SU is the IATA airline designator for Aeroflot, Russia’s flag carrier and largest airline.
-
C.
SU
SU is the station code used to identify Summerhill railway station.
-
D.
SU
SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
-
E.
SU
SU is the common abbreviation for Sofia University "St. Kliment Ohridski," Bulgaria’s oldest and most prestigious higher education institution.
- 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: SU Triple: [Stadtmitte (Bad Honnef), vehicleRegistrationCode, SU]
Generated description
SU is the vehicle registration code for the Rhein-Sieg-Kreis district in the German state of North Rhine-Westphalia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SU Target entity description: SU is the vehicle registration code for the Rhein-Sieg-Kreis district in the German state of North Rhine-Westphalia.
-
A.
SU
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
-
B.
SU
SU is the station code used to identify Summerhill railway station.
-
C.
SU
SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
-
D.
SU
SU is the stock ticker symbol under which Schneider Electric, a global leader in energy management and automation, is traded.
-
E.
SU
SU is the IATA airline designator for Aeroflot, Russia’s flag carrier and largest airline.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e965c9048190804ebb48f0a4817b |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f43633948190b86f5603ac50ec47 |
completed | April 19, 2026, 3:26 p.m. |
| NEDg | Description generation | batch_69e4f9596e1081908e7b319f77453438 |
completed | April 19, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4ff5881b8819080f9662a0c2d486d |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 8, 2026, 9:31 p.m.