Triple
T34978400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Law and the Lady |
E1008745
|
entity |
| Predicate | featuresLegalConcept |
P148110
|
FINISHED |
| Object | Not Proven verdict |
—
|
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: Not Proven verdict | Statement: [The Law and the Lady, featuresLegalConcept, Not Proven verdict]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresLegalConcept Context triple: [The Law and the Lady, featuresLegalConcept, Not Proven verdict]
-
A.
legalConcept
Indicates a relationship where something is classified or treated as a concept defined and governed by law or legal theory.
-
B.
featuresLaw
Indicates that something includes, presents, or is characterized by a particular law or legal provision.
-
C.
legalFeature
chosen
Indicates that something possesses a specific legal characteristic, status, or attribute relevant to laws or regulations.
-
D.
relatedLegalConcept
Indicates that one legal concept is connected or associated with another through a relevant legal relationship or context.
-
E.
legalSystemFeature
Indicates a characteristic, rule, or structural element that forms part of a particular 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.