Triple
T36684195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Third Part |
E905770
|
entity |
| Predicate | hasLegalScope |
P25835
|
FINISHED |
| Object | realm of Castile |
—
|
NE NERFINISHED |
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: realm of Castile | Statement: [Third Part, hasLegalScope, realm of Castile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalScope Context triple: [Third Part, hasLegalScope, realm of Castile]
-
A.
hasRegulationScope
Indicates that a regulation applies to, or governs, a specified scope, domain, or area of relevance.
-
B.
hasLegalSubjectArea
Indicates that something (such as a document, case, or rule) pertains to or is classified under a particular area of law.
-
C.
legalScope
chosen
Indicates the range, boundaries, or extent of authority, applicability, or effect that something has under a particular legal framework or rule.
-
D.
hasScope
Indicates that one entity defines, limits, or encompasses the range, extent, or applicability within which another entity operates or is valid.
-
E.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe6c811bcc81908b1e1b1f8bcb071b |
completed | May 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69fe6c026d5481908b7a814dcf38c183 |
completed | May 8, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:12 p.m.