Triple
T27957406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landesminister |
E703588
|
entity |
| Predicate | untersteht |
P103796
|
FINISHED |
| Object |
Ministerpräsident des Landes
Der Ministerpräsident des Landes ist das Regierungsoberhaupt eines deutschen Bundeslandes und leitet dessen Landesregierung.
|
E1798454
|
NE FINISHED |
How this triple was built (3 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: Ministerpräsident des Landes | Statement: [Landesminister, untersteht, Ministerpräsident des Landes]
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: Ministerpräsident des Landes Triple: [Landesminister, untersteht, Ministerpräsident des Landes]
Generated description
Der Ministerpräsident des Landes ist das Regierungsoberhaupt eines deutschen Bundeslandes und leitet dessen Landesregierung.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: untersteht Context triple: [Landesminister, untersteht, Ministerpräsident des Landes]
-
A.
holdsUnder
Indicates that one entity maintains possession, control, or validity of another entity subject to certain conditions, constraints, or a specific context.
-
B.
underlies
Indicates that one entity serves as a fundamental basis, support, or underlying cause for another entity, condition, or phenomenon.
-
C.
underpins
Indicates that one entity serves as the fundamental basis, support, or justification for another.
-
D.
under
Indicates that one entity is positioned below or beneath another entity, often implying vertical alignment or coverage.
-
E.
underRule
chosen
Indicates that one entity is governed, controlled, or subject to the authority, rules, or dominion of another entity.
- F. None of above.
Provenance (6 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_69ef840c8b2c8190946ae9522774ba51 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a13116ba76c8190ae2cdc60899795d4 |
completed | May 24, 2026, 2:55 p.m. |
| NEDg | Description generation | batch_6a1311f106748190b256e38ceb2481f2 |
completed | May 24, 2026, 2:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a159f7e09a88190a7e25e30dfd87d3d |
completed | May 26, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 7:29 p.m.