Triple
T28984176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France–Belgium border |
E734632
|
entity |
| Predicate | adjacentToBelgianRegion |
P68114
|
FINISHED |
| Object | Flanders |
—
|
NE NERFINISHED |
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: Flanders | Statement: [France–Belgium border, adjacentToBelgianRegion, Flanders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentToBelgianRegion Context triple: [France–Belgium border, adjacentToBelgianRegion, Flanders]
-
A.
includesBelgianRegion
Indicates that one entity geographically or administratively contains or encompasses a region located in Belgium.
-
B.
otherRegionsOfBelgium
Indicates that the related entities are regions of Belgium that are distinct from a specified primary Belgian region.
-
C.
positionInBelgium
Indicates that one entity occupies a specific geographic location within the territory of Belgium.
-
D.
geographicallyAdjacentTo
chosen
Indicates that two geographic entities share a common boundary or are directly next to each other in space.
-
E.
hasNameInBelgium
Indicates that an entity is known or referred to by a particular name specifically within the context of Belgium.
- 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 28, 2026, 9:13 a.m.