Triple
T37008799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seventh Partida |
E915882
|
entity |
| Predicate | hasLegalSubjectMatter |
P196606
|
FINISHED |
| Object | procedural 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: procedural law | Statement: [Seventh Partida, hasLegalSubjectMatter, procedural law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalSubjectMatter Context triple: [Seventh Partida, hasLegalSubjectMatter, procedural law]
-
A.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
-
B.
hasLegalSubjectArea
chosen
Indicates that something (such as a document, case, or rule) pertains to or is classified under a particular area of law.
-
C.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
D.
hasLegalDiscussionIn
Indicates that a legal discussion or proceeding involving an entity takes place within a specified location or context.
-
E.
legalTopicCoverage
Indicates that one entity (such as a document, service, or resource) addresses, discusses, or is relevant to a particular legal topic or area of law.
- 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_69f76e90ed548190b187d2475f5c807d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
Created at: May 3, 2026, 4:14 p.m.