Triple
T19565553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steißlingen |
E489572
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | KN |
—
|
NE NERFINISHED |
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: KN | Statement: [Steißlingen, vehicleRegistrationCode, KN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KN Context triple: [Steißlingen, vehicleRegistrationCode, KN]
-
A.
KN
KN is the ISO 3166-1 alpha-2 country code for Saint Kitts and Nevis, a dual-island nation in the Caribbean.
-
B.
KN
KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
-
C.
KN
KN is the vehicle registration code used for cars registered in the town of Kolárovo in Slovakia.
-
D.
KN
chosen
KN is the vehicle registration code assigned to the city of Konstanz and its surrounding district in the German state of Baden-Württemberg.
-
E.
KEN
KEN is the official FIFA trigramme used to represent the Kenya national football team in international competitions and records.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f777cf081909312b46ac09bce7c |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.