Triple
T1539103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lemon test |
E32822
|
entity |
| Predicate | legalStandardType |
P30149
|
FINISHED |
| Object | three-pronged test |
—
|
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: three-pronged test | Statement: [Lemon test, legalStandardType, three-pronged test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStandardType Context triple: [Lemon test, legalStandardType, three-pronged test]
-
A.
legalCodeType
Indicates the specific category or classification of a legal code that applies to an entity or situation.
-
B.
legalStandardHistoricallyAssociatedWith
Indicates that a particular legal standard has been historically linked or traditionally associated with another legal concept, practice, or context.
-
C.
legalStandardCreated
Indicates that one entity (such as a case, statute, or regulation) establishes or formulates a legal standard that is then applied or referenced by another entity.
-
D.
legalAuthorityType
Indicates the specific kind or category of legal authority that governs, authorizes, or regulates an entity or action.
-
E.
legalCitationType
Indicates the specific kind or category of legal citation that characterizes the relationship between the citing and cited legal sources.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a93df847cc8190b6d011af33b34b40 |
completed | March 5, 2026, 8:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.