Triple
T30485595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Togo–Ghana border region |
E775709
|
entity |
| Predicate | hasPoliticalBoundaryType |
P58557
|
FINISHED |
| Object | international land border |
—
|
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: international land border | Statement: [Togo–Ghana border region, hasPoliticalBoundaryType, international land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalBoundaryType Context triple: [Togo–Ghana border region, hasPoliticalBoundaryType, international land border]
-
A.
isPoliticalBoundary
Indicates that one entity serves as a dividing line or border that separates distinct political or administrative jurisdictions.
-
B.
geographicBoundary
Indicates that one entity serves as a limiting border or edge that defines the geographic extent or separation of another entity.
-
C.
hasLandBoundary
Indicates that one entity shares a common land border with another entity.
-
D.
hasBoundaryUnit
Indicates that one entity uses or is associated with a specific unit of measurement for its boundary or limit.
-
E.
countryBorderType
chosen
Indicates the type or nature of the border relationship that exists between two countries.
- 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_69f22497f91c8190afa7165bc900accd |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: April 29, 2026, 8:13 p.m.