Triple
T3835228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ad Dahna Desert |
E91113
|
entity |
| Predicate | hasRoadCrossings |
P33132
|
FINISHED |
| Object | highways between Riyadh and eastern Saudi Arabia |
—
|
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: highways between Riyadh and eastern Saudi Arabia | Statement: [Ad Dahna Desert, hasRoadCrossings, highways between Riyadh and eastern Saudi Arabia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadCrossings Context triple: [Ad Dahna Desert, hasRoadCrossings, highways between Riyadh and eastern Saudi Arabia]
-
A.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
B.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
C.
crossedByHighway
chosen
Indicates that a highway passes across or through the extent of a given entity or area.
-
D.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
E.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb9a27508190b05e5312cc7c8033 |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.