Triple
T377303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw |
E8399
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
WA
WA is the vehicle registration code used on license plates for cars registered in Warsaw, the capital city of Poland.
|
E117287
|
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: WA | Statement: [Warsaw, vehicleRegistrationCode, WA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WA Context triple: [Warsaw, vehicleRegistrationCode, WA]
-
A.
Washington
Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
-
B.
Washington
Washington is a common English surname most famously borne by George Washington, the first president of the United States.
-
C.
Washington
Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
-
D.
Oregon
Oregon is a U.S. state in the Pacific Northwest known for its diverse landscapes, including rugged coastline, dense forests, mountains, and high desert, as well as its environmentally conscious culture.
-
E.
Wisconsin
Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
- 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: WA Triple: [Warsaw, vehicleRegistrationCode, WA]
Generated description
WA is the vehicle registration code used on license plates for cars registered in Warsaw, the capital city of Poland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WA Target entity description: WA is the vehicle registration code used on license plates for cars registered in Warsaw, the capital city of Poland.
-
A.
Washington
Washington is a U.S. state in the Pacific Northwest known for its diverse landscapes, technology industry centered around Seattle, and significant cultural and economic influence on the West Coast.
-
B.
Washington
Washington is a common English surname most famously borne by George Washington, the first president of the United States.
-
C.
Washington
Washington is a small town in Dutchess County, New York, known for its rural character and the village of Millbrook within its borders.
-
D.
Oregon
Oregon is a U.S. state in the Pacific Northwest known for its diverse landscapes, including rugged coastline, dense forests, mountains, and high desert, as well as its environmentally conscious culture.
-
E.
Wisconsin
Wisconsin is a U.S. state in the Upper Midwest known for its dairy industry, Great Lakes shorelines, and mix of rural landscapes and industrial cities.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec1804108190a1e94526b71289ea |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac256a80f08190841759d0f6132e24 |
completed | March 7, 2026, 1:17 p.m. |
| NEDg | Description generation | batch_69ac2641aee88190985d644563c8f602 |
completed | March 7, 2026, 1:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac26e269b081908398530ad3fa23bc |
completed | March 7, 2026, 1:23 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.