Triple
T16313977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York’s marine and coastal district |
E396126
|
entity |
| Predicate | policyToolFor |
P1652
|
FINISHED |
| Object | state marine fisheries management plans |
—
|
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: state marine fisheries management plans | Statement: [New York’s marine and coastal district, policyToolFor, state marine fisheries management plans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyToolFor Context triple: [New York’s marine and coastal district, policyToolFor, state marine fisheries management plans]
-
A.
policyTool
chosen
Indicates that an entity is a tool, mechanism, or instrument used to design, implement, or enforce a policy.
-
B.
analyzesPolicyTool
Indicates that one entity examines, evaluates, or studies a policy-related tool or instrument to understand its features, effectiveness, or implications.
-
C.
policyElement
Indicates that something is a component or constituent part of a broader policy.
-
D.
policyName
Indicates the specific name or title assigned to a policy associated with an entity.
-
E.
policySetBy
Indicates that a particular policy is established, defined, or determined by a specific entity or authority.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288dd90d4819097bd01a7b40a54cd |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.