Triple
T14336910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French-Belgian border region |
E355488
|
entity |
| Predicate | hasBorderLengthApprox |
P85378
|
FINISHED |
| Object | 620 kilometres |
—
|
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: 620 kilometres | Statement: [French-Belgian border region, hasBorderLengthApprox, 620 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderLengthApprox Context triple: [French-Belgian border region, hasBorderLengthApprox, 620 kilometres]
-
A.
hasBorderLengthCharacteristic
Indicates that a border is associated with a specific length-related property or characteristic.
-
B.
shareBorderLengthApprox
chosen
Indicates that two entities share a common boundary whose length is approximately equal to a specified value.
-
C.
hasBorderElement
Indicates that one entity includes or is associated with another entity that forms part of its boundary or edge.
-
D.
hasBorderThrough
Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
-
E.
hasBorderLocality
Indicates that one locality is situated along or adjacent to the border of another locality.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c2241e48190a0c626b3d741966a |
completed | April 14, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.