Triple
T2438761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Honnef |
E53223
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | SU |
E2716
|
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: SU | Statement: [Bad Honnef, vehicleRegistrationCode, SU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SU Context triple: [Bad Honnef, vehicleRegistrationCode, SU]
-
A.
SU
chosen
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
-
B.
SU
SU is the IATA airline designator for Aeroflot, Russia’s flag carrier and largest airline.
-
C.
Uni
Uni is an Etruscan goddess, broadly equivalent to the Roman Juno and Greek Hera, associated with marriage, fertility, and protection of the state.
-
D.
UA
UA is the commonly used abbreviation for the University of Angers, a French public university located in Angers.
-
E.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f62ad081909373134c5adf65d9 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0b0e920819088bd7ee3684c81fe |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.