Triple
T3105249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anti-Machiavel |
E64814
|
entity |
| Predicate | viewOfLaw |
P21014
|
FINISHED |
| Object | laws should be just and stable |
—
|
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: laws should be just and stable | Statement: [Anti-Machiavel, viewOfLaw, laws should be just and stable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOfLaw Context triple: [Anti-Machiavel, viewOfLaw, laws should be just and stable]
-
A.
viewsLawAs
chosen
Indicates that one entity regards, interprets, or conceptualizes the law in a particular way or from a particular perspective.
-
B.
lawJournal
Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
-
C.
typeOfLaw
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
-
D.
legalCase
Indicates a relationship where a formal legal dispute or proceeding exists between parties, typically adjudicated by a court or similar authority.
-
E.
legalRepresentation
Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada29a90e88190afb8a10291ef1946 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:03 p.m.