Triple
T23342137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saudi national road network |
E591761
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Jeddah |
—
|
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: Jeddah | Statement: [Saudi national road network, serves, Jeddah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeddah Context triple: [Saudi national road network, serves, Jeddah]
-
A.
Jeddah
chosen
Jeddah is a major Saudi Arabian port city on the Red Sea, known as the gateway to the holy cities of Mecca and Medina and a key commercial and cultural hub in the region.
-
B.
Dammam
Dammam is a major Saudi Arabian city and commercial hub on the eastern coast, serving as a key center for the country’s oil industry and maritime trade.
-
C.
Riyadh
Riyadh is the capital and largest city of Saudi Arabia, serving as a major political, economic, and cultural center in the Arab world.
-
D.
Dhahran
Dhahran is a major city in Saudi Arabia’s Eastern Province known for its role as a center of the country’s oil industry and the headquarters of Saudi Aramco.
-
E.
Riyad
Riyad is the given name of Algerian professional footballer Riyad Mahrez, a prominent winger known for his time at Leicester City and Manchester City.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198334dec819081c432b434eb3ba5 |
completed | April 29, 2026, 5:33 a.m. |
Created at: April 17, 2026, 5:18 p.m.