Triple
T9270049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saudi national rail network |
E222800
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | Ras Al Khair |
E528513
|
NE 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: Ras Al Khair | Statement: [Saudi national rail network, connectsWith, Ras Al Khair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ras Al Khair Context triple: [Saudi national rail network, connectsWith, Ras Al Khair]
-
A.
Ras Al Khair
chosen
Ras Al Khair is an industrial city on Saudi Arabia’s eastern coast, known for its major mining, minerals processing, and maritime industries.
-
B.
Ras al-Ghar
Ras al-Ghar is a key coastal military installation in Saudi Arabia that serves as one of the principal bases for the Royal Saudi Naval Forces.
-
C.
Khor Fakkan
Khor Fakkan is a coastal city on the Gulf of Oman in the United Arab Emirates, known for its natural harbor, beaches, and scenic mountainous backdrop.
-
D.
Nad Al Sheba
Nad Al Sheba is a district in Dubai, United Arab Emirates, best known for its major horse racing facilities and upscale residential developments.
-
E.
Ras Tanura
Ras Tanura is a major Saudi Arabian oil port and industrial city on the Persian Gulf, known for its large oil refinery and export facilities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca841ffe208190aa7bcffbef2f8379 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd078525308190abfb883123742d3f |
completed | April 1, 2026, 11:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09c2ca500819083ef4aa37f3e3a7f |
completed | April 4, 2026, 5:05 a.m. |
Created at: March 30, 2026, 7:33 p.m.