Triple
T8292861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stannary courts |
E193941
|
entity |
| Predicate | hasAssociatedLegalCode |
P3013
|
FINISHED |
| Object | stannary law |
—
|
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: stannary law | Statement: [Stannary courts, hasAssociatedLegalCode, stannary law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedLegalCode Context triple: [Stannary courts, hasAssociatedLegalCode, stannary law]
-
A.
hasLegalCodeCharacteristic
Indicates that a legal code possesses a specified characteristic, feature, or property.
-
B.
hasLegalCodeAttributedTo
Indicates that a legal code or body of laws is attributed or assigned to a particular entity as its source, owner, or governing framework.
-
C.
usesLegalCode
chosen
Indicates that one entity applies, references, or operates under a particular legal code in its actions or regulations.
-
D.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
E.
legalCodeName
Indicates that one entity is the official legal code designation or name assigned to another entity within a legal or regulatory 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7c9deb50819086ae9c97b03fefc3 |
completed | March 31, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:52 p.m.