Triple
T9646724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kleve |
E233215
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | KLE |
E457425
|
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: KLE | Statement: [Kleve, vehicleRegistrationCode, KLE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KLE Context triple: [Kleve, vehicleRegistrationCode, KLE]
-
A.
KLE
chosen
KLE is the vehicle registration code for the district of Cleves (Kleve) in the German state of North Rhine-Westphalia.
-
B.
KLEW
KLEW is the ICAO airport code for Auburn/Lewiston Municipal Airport in Maine, United States.
-
C.
KLS
KLS is a research center at Kiel University focused on interdisciplinary life science studies, including molecular biology, medicine, and environmental sciences.
-
D.
KLAL
KLAL is the ICAO airport code for Lakeland Linder International Airport in Lakeland, Florida, a regional airport known for general aviation and cargo operations.
-
E.
KL
KL is the squadron code historically used to identify No. 54 Squadron of the Royal Air Force on its aircraft and operational records.
- 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_69ca848b31648190b57aa55da20285be |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b8122148190bd0af3a04b21e53e |
completed | April 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1825dc8e08190bfc3475cd2e694ba |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:12 p.m.