Triple
T4855645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France and Switzerland |
E108530
|
entity |
| Predicate | haveEconomicTies |
P9483
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [France and Switzerland, haveEconomicTies, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveEconomicTies Context triple: [France and Switzerland, haveEconomicTies, yes]
-
A.
isLinkedEconomicallyTo
chosen
Indicates that two entities are connected through economic relationships such as trade, investment, financial flows, or shared market dependencies.
-
B.
hasEconomicOrganization
Indicates that an entity possesses, is associated with, or participates in a specific economic organization or institutional economic structure.
-
C.
hasEconomicActor
Indicates that an entity participates in or influences an economic activity, process, or system in the role of an economic actor.
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.