Triple
T8641924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badr |
E204670
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Yanbu |
E91777
|
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: Yanbu | Statement: [Badr, near, Yanbu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yanbu Context triple: [Badr, near, Yanbu]
-
A.
Yanbu
chosen
Yanbu is a coastal city in western Saudi Arabia on the Red Sea, known as an industrial and port hub in the Medina Province.
-
B.
Al Bahah
Al Bahah is a city in southwestern Saudi Arabia known for its mild climate, forests, and mountainous landscapes that make it a popular domestic tourist destination.
-
C.
Nasiriyah
Nasiriyah is a significant city in southern Iraq known as a regional administrative center and a hub near several important archaeological sites such as the ancient city of Ur.
-
D.
Rabigh
Rabigh is a coastal city on the Red Sea in western Saudi Arabia known for its industrial complexes, port facilities, and proximity to major pilgrimage and trade routes.
-
E.
Al-Shuwaikh
Al-Shuwaikh is a district in Kuwait City known for its industrial area, port facilities, and commercial activity.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4795b07081908bfc9ebf35a50f07 |
completed | March 31, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccb10f0881908db334cd090d3231 |
completed | April 2, 2026, 8:08 p.m. |
Created at: March 30, 2026, 6:28 p.m.