Triple
T9107501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ha'il |
E218512
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Buraydah |
E191630
|
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: Buraydah | Statement: [Ha'il, roadConnection, Buraydah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buraydah Context triple: [Ha'il, roadConnection, Buraydah]
-
A.
Buraydah
chosen
Buraydah is a major city in central Saudi Arabia and the capital of Al-Qassim Region, known as an important agricultural and commercial center.
-
B.
Fahdah
Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
-
C.
Juwayriya
Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
-
D.
Juhayna
Juhayna is a town in Egypt’s Sohag Governorate, located in Upper Egypt along the Nile Valley.
-
E.
المروة
المروة هو اسم علم عربي يُستخدم غالبًا للإناث ويُستمد من اسم أحد الجبلين في شعائر السعي بين الصفا والمروة في مكة.
- 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_69ca83db7448819090d0a5de842ef2ac |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca573da0081909f4afcdb3ac99c53 |
completed | April 1, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0302bfa00819097e752f1d0581d2d |
completed | April 3, 2026, 9:25 p.m. |
Created at: March 30, 2026, 7:16 p.m.