Triple
T28099448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Workers' Party of Belgium |
E710188
|
entity |
| Predicate | hasStrongTiesWith |
P96771
|
FINISHED |
| Object | Belgian trade unions |
—
|
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: Belgian trade unions | Statement: [Workers' Party of Belgium, hasStrongTiesWith, Belgian trade unions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongTiesWith Context triple: [Workers' Party of Belgium, hasStrongTiesWith, Belgian trade unions]
-
A.
hasStrongTiesTo
chosen
Indicates a close, influential, and enduring relationship or connection exists between the referenced entities.
-
B.
hasSocialTieWith
Indicates a social relationship or connection exists between two entities, such as friendship, acquaintance, or other interpersonal tie.
-
C.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
hasNeighborRelationshipWith
Indicates that one entity is located adjacent to or directly next to another entity, sharing a neighbor relationship.
- 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_69ef9b70fd108190a875953b2e50ca91 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 27, 2026, 9:04 p.m.