Triple
T4783619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMEL |
E106423
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | BMEL |
E106423
|
NE FINISHED |
How this triple was built (2 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: BMEL | Statement: [BMEL, abbreviation, BMEL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BMEL Context triple: [BMEL, abbreviation, BMEL]
-
A.
BMEL
chosen
BMEL is the abbreviation for Germany’s Federal Ministry responsible for national policies on food, agriculture, and consumer protection in these areas.
-
B.
BMBF
BMBF is the German Federal Ministry responsible for national policy and funding in education, science, and research.
-
C.
Empa
Empa is a Swiss federal research institute focused on materials science and technology, known for developing innovative solutions for industry and society.
-
D.
Rentenmark
The Rentenmark was a temporary German currency introduced in 1923 to halt hyperinflation and stabilize the economy during the Weimar Republic.
-
E.
Merksem
Merksem is a northern district of the Belgian city of Antwerp, known as a predominantly residential area with local commerce and sports facilities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ad3a188190872e47e3a3bf504b |
completed | March 20, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43d72e3881909184aeee29b623a0 |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.