Triple
T7159443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comorian franc |
E166900
|
entity |
| Predicate | relationshipWithFrance |
P47199
|
FINISHED |
| Object | monetary cooperation agreement |
—
|
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: monetary cooperation agreement | Statement: [Comorian franc, relationshipWithFrance, monetary cooperation agreement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithFrance Context triple: [Comorian franc, relationshipWithFrance, monetary cooperation agreement]
-
A.
partyRoleOfFrance
Indicates the specific role or capacity that France holds as a party within a given agreement, event, or relationship.
-
B.
joinedFrance
Indicates that an entity became a member of or was incorporated into France.
-
C.
significanceForFrance
Indicates that something holds particular importance, impact, or relevance specifically in the context of France.
-
D.
politicalRelation
chosen
Indicates a relationship between entities that involves political alignment, influence, affiliation, conflict, or cooperation within a political context.
-
E.
strengthFrance
Indicates a relationship where a level, measure, or attribute of strength is associated specifically with France.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e811d6b081909dafeee1d820c74f |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.