Triple
T13441052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanne |
E320360
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | HZ |
E318585
|
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: HZ | Statement: [Tanne, vehicleRegistrationCode, HZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HZ Context triple: [Tanne, vehicleRegistrationCode, HZ]
-
A.
HZ
chosen
HZ is the vehicle registration code assigned to the town of Thale in Germany.
-
B.
ZH
ZH is the provincial code for Zuid-Holland, a densely populated and economically important province in the western Netherlands that includes cities like Rotterdam and The Hague.
-
C.
ZH
ZH is the official vehicle registration code used for the Swiss canton of Zurich.
-
D.
HY
HY is the commonly used abbreviation for the University of Helsinki, a major research university in Finland.
-
E.
HY
HY is the vehicle registration code used on license plates for vehicles registered in the Finnish town of Hyvinkää.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee704ac8190b4c7f4e0d3a88494 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7399421908190a7750e37c89a73f6 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:40 p.m.