Triple
T10163485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autokrator |
E233947
|
entity |
| Predicate | hasConceptualRelation |
P12753
|
FINISHED |
| Object | absolute power |
—
|
LITERAL 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: absolute power | Statement: [Autokrator, hasConceptualRelation, absolute power]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConceptualRelation Context triple: [Autokrator, hasConceptualRelation, absolute power]
-
A.
semanticRelation
chosen
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
B.
hasConceptualParallel
Indicates that one entity corresponds to or mirrors another at a conceptual level, showing a similar idea, structure, or pattern despite possible differences in form or context.
-
C.
hasConceptualStructure
Indicates that one entity embodies, organizes, or is characterized by a particular conceptual structure defined by another entity.
-
D.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
E.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
- F. None of above.
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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec6a7bb48190952f4318af9cc32b |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:09 p.m.