Triple
T8389678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dresden-Neustadt station |
E197909
|
entity |
| Predicate | railwayStationCode |
P1289
|
FINISHED |
| Object |
DDN
DDN is the station code for Dresden-Neustadt, a major railway station in Dresden, Germany.
|
E730750
|
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: DDN | Statement: [Dresden-Neustadt station, railwayStationCode, DDN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DDN Context triple: [Dresden-Neustadt station, railwayStationCode, DDN]
-
A.
DDDN
DDDN is a medical division specializing in the research, diagnosis, and treatment of digestive system and nutritional disorders.
-
B.
DDF
DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
-
C.
DD News
DD News is an Indian 24-hour television news channel operated by the public service broadcaster Doordarshan, providing national and international news coverage.
-
D.
DDM
DDM was the ISO 4217 currency code for the East German mark, the official currency of the former German Democratic Republic.
-
E.
DDC
DDC is the Dart Dev Compiler, a tool that compiles Dart code to efficient JavaScript for web development.
- 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: DDN Triple: [Dresden-Neustadt station, railwayStationCode, DDN]
Generated description
DDN is the station code for Dresden-Neustadt, a major railway station in Dresden, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DDN Target entity description: DDN is the station code for Dresden-Neustadt, a major railway station in Dresden, Germany.
-
A.
DDDN
DDDN is a medical division specializing in the research, diagnosis, and treatment of digestive system and nutritional disorders.
-
B.
DDF
DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
-
C.
DD News
DD News is an Indian 24-hour television news channel operated by the public service broadcaster Doordarshan, providing national and international news coverage.
-
D.
DDM
DDM was the ISO 4217 currency code for the East German mark, the official currency of the former German Democratic Republic.
-
E.
DDC
DDC is the IATA airport code for Dodge City Regional Airport, a public airport serving Dodge City in southwestern Kansas, United States.
- 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_69ca82f749388190bffbea6dfb509016 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb810ac380819095bd67f0555ac2a8 |
completed | March 31, 2026, 8:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde84427dc8190925150b5d52bc9a0 |
completed | April 2, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_69cdebfc63e8819087f5c1d588b58e21 |
completed | April 2, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cded77618c81909e8786ccd2f3e4b6 |
completed | April 2, 2026, 4:15 a.m. |
Created at: March 30, 2026, 6:03 p.m.