Triple
T27591450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open Policy Agent |
E699796
|
entity |
| Predicate | supportsPolicyLanguage |
P199615
|
FINISHED |
| Object | Rego |
—
|
NE NERFINISHED |
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: Rego | Statement: [Open Policy Agent, supportsPolicyLanguage, Rego]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPolicyLanguage Context triple: [Open Policy Agent, supportsPolicyLanguage, Rego]
-
A.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
B.
usesLanguageSupport
Indicates that one entity makes use of language-related assistance, features, or services provided by another entity.
-
C.
hasLanguagePolicyLink
Indicates that there is a specific URL or reference link associated with an entity that points to its language policy.
-
D.
hasOfficialLanguagePolicy
Indicates that there exists a formally adopted rule or set of rules governing the use, status, or regulation of one or more languages within a given context or jurisdiction.
-
E.
hasLanguagePolicyContext
Indicates that there is an associated language-related policy, rule, or regulatory context governing how language is used or managed in relation to the subject.
- 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_69ef6a4d71f081909a1235763206b691 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69ff49016dcc8190a8a43868c728b4f1 |
completed | May 9, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69ff4891924c8190b5be340e2520e012 |
completed | May 9, 2026, 2:45 p.m. |
| PDg | Predicate description generation | batch_69ff490096388190832a90e9abbc8d81 |
completed | May 9, 2026, 2:47 p.m. |
Created at: April 27, 2026, 2:05 p.m.