Triple
T9093923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baselland |
E217964
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | BL |
E145802
|
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: BL | Statement: [Baselland, vehicleRegistrationCode, BL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BL Context triple: [Baselland, vehicleRegistrationCode, BL]
-
A.
BL
chosen
BL is the vehicle registration code used on license plates for the Swiss canton of Basel-Landschaft.
-
B.
BL
BL is the two-letter ISO 3166-1 alpha-2 country code assigned to the Caribbean island territory of Saint Barthélemy.
-
C.
BL
BL is the vehicle registration code used on license plates for vehicles registered in the Bratislava Region of Slovakia.
-
D.
BL
BL is the vehicle registration code used for the city of Banja Luka in Bosnia and Herzegovina.
-
E.
BL
BL is the commonly used abbreviation for British Leyland, a major former UK vehicle manufacturer known for producing a wide range of cars, trucks, and buses in the 20th century.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b347d4819085b33d0e20834f47 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d01803b0288190a86b544892d4b6ed |
completed | April 3, 2026, 7:41 p.m. |
Created at: March 30, 2026, 7:14 p.m.