Triple
T37306024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reine Rechtslehre |
E926081
|
entity |
| Predicate | treatsStateAs |
P175880
|
FINISHED |
| Object | order of legal norms |
—
|
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: order of legal norms | Statement: [Reine Rechtslehre, treatsStateAs, order of legal norms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsStateAs Context triple: [Reine Rechtslehre, treatsStateAs, order of legal norms]
-
A.
regardsTheStateAs
chosen
Indicates viewing or treating the state in a particular way, typically expressing an attitude, judgment, or evaluative stance toward it.
-
B.
taxTreatmentState
Indicates the specific way an item, transaction, or entity is handled or classified under a particular state's tax rules and regulations.
-
C.
refersToStateOf
Indicates that one entity denotes, describes, or is about the condition, status, or situation (state) of another entity.
-
D.
separatesState
Indicates that one entity serves as a dividing boundary or barrier between two distinct states or regions.
-
E.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.