Triple
T8708184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evidence |
E206703
|
entity |
| Predicate | hasLegalAndPoliticalElements |
P84660
|
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: [Evidence, hasLegalAndPoliticalElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalAndPoliticalElements Context triple: [Evidence, hasLegalAndPoliticalElements, true]
-
A.
hasLegislativeSubject
Indicates that a legislative document, action, or body concerns, addresses, or is about a particular subject or topic.
-
B.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
-
C.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
-
D.
includesLegalFramework
Indicates that one entity encompasses, references, or incorporates a specific legal framework within its scope or content.
-
E.
hasLegalEffect
Indicates that an action, document, or condition produces recognized legal consequences or enforceable rights and obligations.
- 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_69ca835645e881908f00e3c8b51da81d |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc58ffa6a481908866b6239d1d9b92 |
completed | March 31, 2026, 11:30 p.m. |
| PD | Predicate disambiguation | batch_69cc456bda508190a9aa0fb92760739e |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc582412f48190ae819965bfb0e75d |
completed | March 31, 2026, 11:26 p.m. |
Created at: March 30, 2026, 6:35 p.m.