Triple
T25275942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunduma–Nakonde border |
E633695
|
entity |
| Predicate | railCrossingBetween |
P158322
|
FINISHED |
| Object | Tanzania |
—
|
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: Tanzania | Statement: [Tunduma–Nakonde border, railCrossingBetween, Tanzania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railCrossingBetween Context triple: [Tunduma–Nakonde border, railCrossingBetween, Tanzania]
-
A.
hasRailwayCrossing
Indicates that a location or route includes a point where a railway line and a road or path intersect, typically at the same level.
-
B.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
C.
hasMajorRailCrossing
Indicates that there is a significant railway crossing (such as a major rail line intersecting a road or another transport route) at or associated with the referenced location or entity.
-
D.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
E.
mainRoadCrossingBetween
Indicates that a primary or main road intersects or passes between two specified locations or entities.
- F. None of above. chosen
Provenance (4 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48ba6156481909e0b7e9965b4bc48 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:17 p.m.