Triple
T14511217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Daayen Municipality |
E340398
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Al Kheesa
Al Kheesa is a village in the Al Daayen region of Qatar that has rapidly developed from a traditional settlement into a growing suburban area near Doha.
|
E1105582
|
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 Kheesa | Statement: [Al Daayen Municipality, contains, Al Kheesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Al Kheesa Context triple: [Al Daayen Municipality, contains, Al Kheesa]
-
A.
Al Khurmah
Al Khurmah is a town in western Saudi Arabia situated within the Makkah Province.
-
B.
Al Majarrah
Al Majarrah is a waterfront district in Sharjah, United Arab Emirates, known for its cultural landmarks and museums.
-
C.
El Qurein
El Qurein is a city in Egypt’s Sharqia Governorate, known as a local administrative and population center in the eastern Nile Delta region.
-
D.
Al Dafna
Al Dafna is a prominent business and commercial district in Doha, Qatar, known for its modern skyscrapers and waterfront location along the Doha Corniche.
-
E.
Mesaieed
Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
- 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 Kheesa Triple: [Al Daayen Municipality, contains, Al Kheesa]
Generated description
Al Kheesa is a village in the Al Daayen region of Qatar that has rapidly developed from a traditional settlement into a growing suburban area near Doha.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Al Kheesa Target entity description: Al Kheesa is a village in the Al Daayen region of Qatar that has rapidly developed from a traditional settlement into a growing suburban area near Doha.
-
A.
Al Khurmah
Al Khurmah is a town in western Saudi Arabia situated within the Makkah Province.
-
B.
Al Majarrah
Al Majarrah is a waterfront district in Sharjah, United Arab Emirates, known for its cultural landmarks and museums.
-
C.
El Qurein
El Qurein is a city in Egypt’s Sharqia Governorate, known as a local administrative and population center in the eastern Nile Delta region.
-
D.
Al Dafna
Al Dafna is a prominent business and commercial district in Doha, Qatar, known for its modern skyscrapers and waterfront location along the Doha Corniche.
-
E.
Mesaieed
Mesaieed is an industrial city in Qatar known for its major port facilities and petrochemical industries.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6c6054819086b4c0ce1d83fdc5 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8aaeaf40819087fa0db989813e02 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8b5929c08190ae4596a23857ed06 |
completed | May 8, 2026, 7:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8beb5d608190b4825ccb0935f041 |
completed | May 8, 2026, 7:08 a.m. |
Created at: April 10, 2026, 1:21 a.m.