Triple
T753256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union for the Mediterranean |
E15495
|
entity |
| Predicate | focusesOnPolicyArea |
P1876
|
FINISHED |
| Object | economic development |
—
|
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: economic development | Statement: [Union for the Mediterranean, focusesOnPolicyArea, economic development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnPolicyArea Context triple: [Union for the Mediterranean, focusesOnPolicyArea, economic development]
-
A.
commonPolicyArea
Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
-
B.
coversPolicyArea
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
-
C.
policyFocus
chosen
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
D.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
E.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64d7d2c8190a6059adcb8fbd34f |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.