Triple
T10968542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waldeck-Frankenberg |
E259169
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | KB |
E7657
|
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: KB | Statement: [Waldeck-Frankenberg, vehicleRegistrationCode, KB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KB Context triple: [Waldeck-Frankenberg, vehicleRegistrationCode, KB]
-
A.
KB
chosen
KB is a distinct entity from Kt, likely representing a separate concept, object, or identifier within the same domain.
-
B.
k_B
k_B is the conventional symbol used to denote the Boltzmann constant, a fundamental physical constant that relates temperature to energy at the particle level.
-
C.
KBKW
KBKW is the ICAO airport code for Raleigh County Memorial Airport in Beckley, West Virginia, United States.
-
D.
KBV
KBV is the IATA airport code for Krabi International Airport, a major gateway to Thailand’s Krabi province and nearby Andaman Sea destinations.
-
E.
KN
KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7719800388190943a0bffa48a2731 |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d78156c48190a956dc22b9832bcb |
completed | April 18, 2026, 12:59 a.m. |
Created at: April 8, 2026, 9:24 p.m.