Triple
T28170456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R. v. Lavell |
E715442
|
entity |
| Predicate | isLandmarkCase |
P9728
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [R. v. Lavell, isLandmarkCase, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLandmarkCase Context triple: [R. v. Lavell, isLandmarkCase, true]
-
A.
landmarkCase
chosen
Indicates that a legal case is historically significant or precedent-setting within a legal system.
-
B.
judgeInLandmarkCase
Indicates that a person served as a judge in a court case recognized as historically or legally significant.
-
C.
isLandmarkEvent
Indicates that an event is recognized as a significant or notable occurrence, often marking an important milestone or turning point.
-
D.
isLandmarkFor
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
E.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
- 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641def1e88190a05bf865ced78b23 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:12 p.m.