Triple
T4128960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Waldsee |
E84993
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
RV
RV is the vehicle registration code assigned to the town of Bad Waldsee in the Ravensburg district of Germany.
|
E416137
|
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: RV | Statement: [Bad Waldsee, vehicleRegistrationCode, RV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RV Context triple: [Bad Waldsee, vehicleRegistrationCode, RV]
-
A.
RV
RV is a 2006 family road-trip comedy film starring Robin Williams as a father trying to reconnect with his family during a chaotic vacation in a rented recreational vehicle.
-
B.
RV Kairei
RV Kairei is a Japanese deep-sea research vessel operated by JAMSTEC, known for conducting advanced oceanographic and seafloor exploration in some of the world’s deepest waters.
-
C.
Winnebago
Winnebago is the former English name for the Ho-Chunk, a Native American people originally from the Wisconsin and Illinois region.
-
D.
TRV
TRV is the stock ticker symbol for The Travelers Companies, a major U.S.-based insurance provider known for its property and casualty insurance products.
-
E.
RV Calypso
RV Calypso was Jacques Cousteau’s famous oceanographic research vessel, renowned for pioneering undersea exploration and marine science.
- 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: RV Triple: [Bad Waldsee, vehicleRegistrationCode, RV]
Generated description
RV is the vehicle registration code assigned to the town of Bad Waldsee in the Ravensburg district of Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RV Target entity description: RV is the vehicle registration code assigned to the town of Bad Waldsee in the Ravensburg district of Germany.
-
A.
RV
RV is a 2006 family road-trip comedy film starring Robin Williams as a father trying to reconnect with his family during a chaotic vacation in a rented recreational vehicle.
-
B.
RV Kairei
RV Kairei is a Japanese deep-sea research vessel operated by JAMSTEC, known for conducting advanced oceanographic and seafloor exploration in some of the world’s deepest waters.
-
C.
Winnebago
Winnebago is the former English name for the Ho-Chunk, a Native American people originally from the Wisconsin and Illinois region.
-
D.
TRV
TRV is the stock ticker symbol for The Travelers Companies, a major U.S.-based insurance provider known for its property and casualty insurance products.
-
E.
RV Calypso
RV Calypso was Jacques Cousteau’s famous oceanographic research vessel, renowned for pioneering undersea exploration and marine science.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af021c5ca48190a829bab07dda55d0 |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576bf503c8190be44139a908ee42d |
completed | March 14, 2026, 2:54 p.m. |
| NEDg | Description generation | batch_69b577ac31888190b6182b00bd5c709f |
completed | March 14, 2026, 2:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b57839ee548190804ef306fc9b3a6e |
completed | March 14, 2026, 3:01 p.m. |
Created at: March 9, 2026, 3:42 p.m.