Triple
T10215674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havelland |
E242434
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
HVL
HVL is the vehicle registration code used for motor vehicles registered in the Havelland district of Brandenburg, Germany.
|
E850086
|
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: HVL | Statement: [Havelland, hasVehicleRegistrationCode, HVL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HVL Context triple: [Havelland, hasVehicleRegistrationCode, HVL]
-
A.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
B.
BVL
BVL is Germany’s Federal Office of Consumer Protection and Food Safety, the national authority responsible for ensuring food safety and protecting consumer health.
-
C.
TAVHL
TAVHL is the stock ticker symbol for TAV Airports Holding, a Turkish company that develops and operates airport terminals and related services.
-
D.
HV
HV is the IATA airline designator used by Transavia, a Dutch low-cost carrier operating scheduled and charter flights across Europe and surrounding regions.
-
E.
HLF
HLF is the stock ticker symbol for Herbalife, a global multi-level marketing company that sells nutritional supplements and personal care products.
- 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: HVL Triple: [Havelland, hasVehicleRegistrationCode, HVL]
Generated description
HVL is the vehicle registration code used for motor vehicles registered in the Havelland district of Brandenburg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HVL Target entity description: HVL is the vehicle registration code used for motor vehicles registered in the Havelland district of Brandenburg, Germany.
-
A.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
B.
BVL
BVL is Germany’s Federal Office of Consumer Protection and Food Safety, the national authority responsible for ensuring food safety and protecting consumer health.
-
C.
TAVHL
TAVHL is the stock ticker symbol for TAV Airports Holding, a Turkish company that develops and operates airport terminals and related services.
-
D.
HV
HV is the IATA airline designator used by Transavia, a Dutch low-cost carrier operating scheduled and charter flights across Europe and surrounding regions.
-
E.
HLF
HLF is the stock ticker symbol for Herbalife, a global multi-level marketing company that sells nutritional supplements and personal care products.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa2894d0819095704449ecc2db6c |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652f1ffb88190986ea53749fc5e03 |
completed | April 8, 2026, 1:06 p.m. |
| NEDg | Description generation | batch_69d656d55ff481909b84c033aa0f0fc2 |
completed | April 8, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d658a657488190ab08071889af4fb6 |
completed | April 8, 2026, 1:31 p.m. |
Created at: April 6, 2026, 11:05 a.m.