Triple
T10806202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senftenberg |
E254972
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
OSL
OSL is the vehicle registration code for the district of Oberspreewald-Lausitz in the German state of Brandenburg.
|
E886737
|
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: OSL | Statement: [Senftenberg, vehicleRegistrationCode, OSL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OSL Context triple: [Senftenberg, vehicleRegistrationCode, OSL]
-
A.
OSL
OSL is the three-letter IATA airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital.
-
B.
OSO
OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
-
C.
O.S.A.
O.S.A. is the standard post-nominal abbreviation used for members of the Order of Saint Augustine, a Roman Catholic religious order.
-
D.
OSED
OSED is an advanced exploit development certification from Offensive Security that validates a professional’s ability to discover and develop exploits for modern software vulnerabilities.
-
E.
Cal OES
Cal OES is the California state agency responsible for coordinating emergency management, disaster response, and homeland security efforts.
- 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: OSL Triple: [Senftenberg, vehicleRegistrationCode, OSL]
Generated description
OSL is the vehicle registration code for the district of Oberspreewald-Lausitz in the German state of Brandenburg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OSL Target entity description: OSL is the vehicle registration code for the district of Oberspreewald-Lausitz in the German state of Brandenburg.
-
A.
OSL
OSL is the three-letter IATA airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital.
-
B.
OSO
OSO is the commonly used abbreviation for the Office of SIGINT Operations, a signals intelligence unit within the U.S. National Security Agency.
-
C.
O.S.A.
O.S.A. is the standard post-nominal abbreviation used for members of the Order of Saint Augustine, a Roman Catholic religious order.
-
D.
OSED
OSED is an advanced exploit development certification from Offensive Security that validates a professional’s ability to discover and develop exploits for modern software vulnerabilities.
-
E.
Cal OES
Cal OES is the California state agency responsible for coordinating emergency management, disaster response, and homeland security efforts.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b3f92c8190bcc85db22d77bb7d |
completed | April 9, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de5680566c8190bd4ce7a736dc0e46 |
completed | April 14, 2026, 3 p.m. |
| NEDg | Description generation | batch_69de5eaf3cc08190935cb6ddf2020166 |
completed | April 14, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de63a902f4819089845bc6d7469c6b |
completed | April 14, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:18 p.m.