Triple
T18561115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semendo people |
E453639
|
entity |
| Predicate | useAdatLawInLandMatters |
P132158
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Semendo people, useAdatLawInLandMatters, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: useAdatLawInLandMatters Context triple: [Semendo people, useAdatLawInLandMatters, yes]
-
A.
appliedLawFrom
Indicates that a specific law or legal provision was applied or derived from a particular source, context, or jurisdiction in a legal decision or situation.
-
B.
appliesLawThrough
Indicates that one entity enforces, implements, or carries out a law or legal rule by means of another entity or mechanism.
-
C.
legalArea
Indicates the specific field or branch of law that a legal matter, case, or document pertains to.
-
D.
usedLegalSystemOf
Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
-
E.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
- F. None of above. chosen
Provenance (4 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5380a46f08190afe7ca2ddfe209d5 |
completed | April 19, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2b93bc8190a6070018d7046547 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:42 a.m.