Triple
T33689492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | رهط |
E863136
|
entity |
| Predicate | تربطها_طرق |
P170603
|
FINISHED |
| Object | شبكة طرق مع مدينة بئر السبع |
—
|
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: شبكة طرق مع مدينة بئر السبع | Statement: [رهط, تربطها_طرق, شبكة طرق مع مدينة بئر السبع]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: تربطها_طرق Context triple: [رهط, تربطها_طرق, شبكة طرق مع مدينة بئر السبع]
-
A.
linkedByRoadTo
Indicates that two locations are directly connected to each other by a road suitable for travel.
-
B.
roadAssociatedWith
Indicates that there is a relevant connection or linkage between a road and another entity, such as use, location, function, or impact.
-
C.
relatedRoadCar
Indicates that there is a contextual or functional association between a specific road and a specific car (e.g., the car uses, is located on, or is otherwise linked to that road).
-
D.
connectsRoadNetwork
chosen
Indicates that one entity is linked to another as part of the same road network, enabling continuous vehicular or transport connectivity between them.
-
E.
routeOf
Indicates that one entity is the path, course, or trajectory taken or followed by another entity (such as a vehicle, shipment, or signal).
- 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_69f3498662b48190904442c39df84fb7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fa67cd908190a1784bd212fe3749 |
completed | May 3, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.