Triple
T561205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qatar |
E13453
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Al Rayyan
Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
|
E81825
|
NE FINISHED |
How this triple was built (4 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: Al Rayyan | Statement: [Qatar, hasMajorCity, Al Rayyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al Rayyan Context triple: [Qatar, hasMajorCity, Al Rayyan]
-
A.
Doha
Doha is the rapidly developing capital and largest city of Qatar, known for its modern skyline, cultural institutions, and role as a major political and economic center in the Arab world.
-
B.
Diriyah
Diriyah is a historic town in Saudi Arabia that served as the original home of the Saudi royal family and the capital of the first Saudi state.
-
C.
Kuwait City
Kuwait City is the capital and largest city of Kuwait, serving as a major political, economic, and cultural center on the Persian Gulf.
-
D.
al-Wasta
al-Wasta is a town in Egypt’s Beni Suef Governorate, located in Upper Egypt along the Nile River.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Al Rayyan Triple: [Qatar, hasMajorCity, Al Rayyan]
Generated description
Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Al Rayyan Target entity description: Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
-
A.
Doha
Doha is the rapidly developing capital and largest city of Qatar, known for its modern skyline, cultural institutions, and role as a major political and economic center in the Arab world.
-
B.
Diriyah
Diriyah is a historic town in Saudi Arabia that served as the original home of the Saudi royal family and the capital of the first Saudi state.
-
C.
Kuwait City
Kuwait City is the capital and largest city of Kuwait, serving as a major political, economic, and cultural center on the Persian Gulf.
-
D.
al-Wasta
al-Wasta is a town in Egypt’s Beni Suef Governorate, located in Upper Egypt along the Nile River.
-
E.
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.
- F. None of above. chosen
Provenance (5 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499e2795c8190903240e79964156d |
completed | March 1, 2026, 7:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5914232c481909a39cd3373e3c6c9 |
completed | March 2, 2026, 1:31 p.m. |
| NEDg | Description generation | batch_69a5928fbf0c8190b7a76511be48c331 |
completed | March 2, 2026, 1:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a592eb19248190ada0809873de4779 |
completed | March 2, 2026, 1:38 p.m. |
Created at: March 1, 2026, 7:32 p.m.