Triple
T8389633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dresden Airport |
E197908
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
DRS
DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
|
E730747
|
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: DRS | Statement: [Dresden Airport, IATAcode, DRS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DRS Context triple: [Dresden Airport, IATAcode, DRS]
-
A.
DRS
DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
-
B.
DRS Technologies
DRS Technologies was a U.S.-based defense and aerospace company specializing in military electronics and integrated systems, later rebranded as Leonardo DRS after its acquisition by the Italian defense group Leonardo.
-
C.
DRA
DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
-
D.
DHR
DHR is the stock ticker symbol for Danaher Corporation, a global science and technology company focused on life sciences, diagnostics, and environmental and applied solutions.
-
E.
DRES
DRES is a university-based program that provides support services and accommodations to students with disabilities to ensure equal access to education.
- 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: DRS Triple: [Dresden Airport, IATAcode, DRS]
Generated description
DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DRS Target entity description: DRS is the three-letter IATA airport code for Dresden Airport in Dresden, Germany.
-
A.
DRS
DRS is the stock ticker symbol for Leonardo DRS, an American defense technology company specializing in advanced military and intelligence systems.
-
B.
DRS Technologies
DRS Technologies was a U.S.-based defense and aerospace company specializing in military electronics and integrated systems, later rebranded as Leonardo DRS after its acquisition by the Italian defense group Leonardo.
-
C.
DRA
DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
-
D.
DHR
DHR is the stock ticker symbol for Danaher Corporation, a global science and technology company focused on life sciences, diagnostics, and environmental and applied solutions.
-
E.
DRES
DRES is a university-based program that provides support services and accommodations to students with disabilities to ensure equal access to education.
- 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.