Triple
T1673898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgenlandkreis |
E36186
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
NMB
NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
|
E189701
|
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: NMB | Statement: [Burgenlandkreis, vehicleRegistrationCode, NMB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NMB Context triple: [Burgenlandkreis, vehicleRegistrationCode, NMB]
-
A.
NAM
NAM is the commonly used abbreviation for the Non-Aligned Movement, an international grouping of states that sought to remain independent from major power blocs during the Cold War and beyond.
-
B.
NAM
NAM is the commonly used acronym for the National Academy of Medicine, a leading U.S. nonprofit institution that provides expert advice on health, medicine, and biomedical science.
-
C.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
D.
N
The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
-
E.
NH
NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
- 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: NMB Triple: [Burgenlandkreis, vehicleRegistrationCode, NMB]
Generated description
NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NMB Target entity description: NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
-
A.
NAM
NAM is the commonly used acronym for the National Academy of Medicine, a leading U.S. nonprofit institution that provides expert advice on health, medicine, and biomedical science.
-
B.
NAM
NAM is the commonly used abbreviation for the Non-Aligned Movement, an international grouping of states that sought to remain independent from major power blocs during the Cold War and beyond.
-
C.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
-
D.
N
The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
-
E.
NH
NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6246753081909dace4eacf9cb1c0 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71b341bc8190b79f76f426dfa7dd |
completed | March 8, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_69ad735efb0081909bacb7fc0f2d7cbd |
completed | March 8, 2026, 1:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad73b461148190b7b9d9d07233223b |
completed | March 8, 2026, 1:03 p.m. |
Created at: March 4, 2026, 7:29 p.m.