Triple
T9067472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book Seven – Evidence |
E217278
|
entity |
| Predicate | legalSourceType |
P6527
|
FINISHED |
| Object | codified statute |
—
|
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: codified statute | Statement: [Book Seven – Evidence, legalSourceType, codified statute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSourceType Context triple: [Book Seven – Evidence, legalSourceType, codified statute]
-
A.
legalCodeType
Indicates the specific category or classification of a legal code that applies to an entity or situation.
-
B.
legalCitationType
Indicates the specific kind or category of legal citation that characterizes the relationship between the citing and cited legal sources.
-
C.
legalStandardType
Indicates the specific type or category of legal standard that governs or applies to a given legal rule, decision, or evaluation.
-
D.
legalForm
Indicates the specific legal structure or organizational type under which an entity is formally constituted and recognized by law.
-
E.
typeOfLaw
chosen
Indicates that one entity is a specific category or kind of law to which the other entity pertains.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc94bf4f2881908c881e6ee7203994 |
completed | April 1, 2026, 3:45 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:11 p.m.