Triple
T11127772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Aqiq |
E263192
|
entity |
| Predicate | vehicleRegistrationCodeCountry |
P1173
|
FINISHED |
| Object | SA |
E42283
|
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: SA | Statement: [Al Aqiq, vehicleRegistrationCodeCountry, SA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SA Context triple: [Al Aqiq, vehicleRegistrationCodeCountry, SA]
-
A.
SA
The SA (Sturmabteilung) was the Nazi Party’s paramilitary organization known for its role in Adolf Hitler’s rise to power through intimidation, street violence, and mass rallies in early 20th-century Germany.
-
B.
SA
chosen
SA is the two-letter ISO 3166-1 alpha-2 country code representing the Kingdom of Saudi Arabia.
-
C.
SA
SA is a UK postcode area covering Swansea and surrounding parts of South West Wales.
-
D.
SA
SA is a key 3GPP technical specification group responsible for defining the overall system architecture and service capabilities of mobile telecommunications networks.
-
E.
SA
SA is the IATA airline code assigned to South African Airways, the flag carrier airline of South Africa.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e830e804819097fcc3826d84dab8 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d8b3ce4819082f9efcf8dec4f1a |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 8, 2026, 9:28 p.m.