Triple
T16482249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfäfers |
E400348
|
entity |
| Predicate | hasCantonCode |
P28599
|
FINISHED |
| Object | SG |
E475293
|
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: SG | Statement: [Pfäfers, hasCantonCode, SG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SG Context triple: [Pfäfers, hasCantonCode, SG]
-
A.
SG
chosen
SG is the vehicle registration code used on license plates for the Swiss canton of St. Gallen.
-
B.
SG
SG is the vehicle registration code used on license plates for cars registered in Gliwice, Poland.
-
C.
SG
SG is the vehicle registration code used on license plates for Spain’s Segovia Province.
-
D.
SG
SG is a postcode area in the United Kingdom covering parts of Hertfordshire and surrounding regions.
-
E.
SG
SG is the Secretariat-General of the European Commission, the central administrative body that supports the Commission’s work, coordination, and decision-making processes.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e03643881908b16ddb9004af5d0 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581ebe888190a331974473f1be1a |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:13 a.m.