Triple
T3722666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sucha Beskidzka |
E81673
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | KSU |
E81673
|
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: KSU | Statement: [Sucha Beskidzka, hasVehicleRegistrationCode, KSU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KSU Context triple: [Sucha Beskidzka, hasVehicleRegistrationCode, KSU]
-
A.
KSU
KSU is the vehicle registration code used for motor vehicles registered in Kristiansund, Norway.
-
B.
KSU
chosen
KSU is the vehicle registration code used on license plates for the town of Sucha Beskidzka in Poland.
-
C.
Kennesaw State University
Kennesaw State University is a large public research university in Georgia known for its diverse academic programs and rapidly growing student population.
-
D.
KU
KU is the commonly used abbreviation for Korea University, one of South Korea’s leading private research universities.
-
E.
KU
KU is a common abbreviation for the University of Karachi, a major public research university in Karachi, Pakistan.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca9ea1688190b3b8414d77960e8f |
completed | March 8, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce1b25088190958c427c932641e1 |
completed | March 14, 2026, 2:55 a.m. |
Created at: March 8, 2026, 3:34 p.m.