Triple
T14681581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universität des Saarlandes |
E344798
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | DFG |
E43147
|
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: DFG | Statement: [Universität des Saarlandes, memberOf, DFG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DFG Context triple: [Universität des Saarlandes, memberOf, DFG]
-
A.
DFG
chosen
DFG is Germany’s central self-governing research funding organization, supporting scientific and academic research across all disciplines.
-
B.
DFG
DFG is the Massachusetts state agency responsible for conserving and managing fish, wildlife, and related natural resources.
-
C.
DGF
DGF is the vehicle registration code used for the Dingolfing-Landau district in Bavaria, Germany.
-
D.
DFGP
DFGP is the German abbreviation for Switzerland’s Federal Department of Justice and Police, the federal authority responsible for justice, security, and migration matters.
-
E.
DF
DF is the vehicle registration code for Brazil’s Federal District, which includes the national capital, Brasília.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb56a51ec8190941684fd562a7182 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde182dab08190aac2ff2db666ee69 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:28 a.m.