Triple
T16378185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stasi Records Law |
E397730
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
StUG
StUG is the German abbreviation for the Stasi Records Law, which governs access to and handling of the files of the former East German secret police.
|
E1211000
|
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: StUG | Statement: [Stasi Records Law, shortName, StUG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: StUG Context triple: [Stasi Records Law, shortName, StUG]
-
A.
STG
STG is the National Rail station code for Stirling railway station in Stirling, Scotland.
-
B.
SS-Sturm
SS-Sturm was a basic company-sized paramilitary unit of the Nazi Schutzstaffel (SS), typically comprising several platoons within the broader SS organizational structure.
-
C.
SS-Standarten
SS-Standarten were early regimental-level units of the Nazi Schutzstaffel (SS) that served as the organizational and operational foundation for later militarized SS formations.
-
D.
STU
STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
-
E.
Steng
Steng is the family name of Austrian actor and director Klaus Maria Brandauer, known for his acclaimed performances in European cinema and Hollywood films.
- 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: StUG Triple: [Stasi Records Law, shortName, StUG]
Generated description
StUG is the German abbreviation for the Stasi Records Law, which governs access to and handling of the files of the former East German secret police.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: StUG Target entity description: StUG is the German abbreviation for the Stasi Records Law, which governs access to and handling of the files of the former East German secret police.
-
A.
STG
STG is the National Rail station code for Stirling railway station in Stirling, Scotland.
-
B.
SS-Sturm
SS-Sturm was a basic company-sized paramilitary unit of the Nazi Schutzstaffel (SS), typically comprising several platoons within the broader SS organizational structure.
-
C.
SS-Standarten
SS-Standarten were early regimental-level units of the Nazi Schutzstaffel (SS) that served as the organizational and operational foundation for later militarized SS formations.
-
D.
STU
STU is a major public technical university in Bratislava, Slovakia, known for its engineering, technology, and applied science programs.
-
E.
Steng
Steng is the family name of Austrian actor and director Klaus Maria Brandauer, known for his acclaimed performances in European cinema and Hollywood films.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319d97e00819094aa094f52a5a93e |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356658e881908131a3c60ed5499d |
completed | May 10, 2026, 7:36 a.m. |
| NEDg | Description generation | batch_6a00383a7180819092ea605aa8ef1672 |
completed | May 10, 2026, 7:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00391645ac819092a06dc6813604fa |
completed | May 10, 2026, 7:51 a.m. |
Created at: April 10, 2026, 5:08 a.m.