Triple
T17011108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Národní třída metro station |
E412700
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | NB |
E872954
|
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: NB | Statement: [Národní třída metro station, hasStationCode, NB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NB Context triple: [Národní třída metro station, hasStationCode, NB]
-
A.
NB
NB is the official two-letter Canada Post abbreviation for the province of New Brunswick.
-
B.
NB
NB is the standard abbreviation for the Dutch province of North Brabant (Noord-Brabant).
-
C.
NB
chosen
NB is the regional vehicle registration code assigned to the town of Milovice in the Czech Republic.
-
D.
NB
NB is the official abbreviation for the Swiss National Library, the central institution responsible for collecting and preserving Switzerland’s published cultural heritage.
-
E.
BN
BN is the vehicle registration code used on license plates for the German city of Bonn.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d47bcb508190a799f0bad6b70245 |
completed | April 18, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc241ec88190a3e868ab88b26f09 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:33 a.m.