Triple
T13137878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vienenburg |
E312129
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | GS |
E256505
|
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: GS | Statement: [Vienenburg, hasVehicleRegistrationCode, GS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GS Context triple: [Vienenburg, hasVehicleRegistrationCode, GS]
-
A.
GS
GS is the common abbreviation for United Global Services, United Airlines’ invitation-only elite frequent flyer status for its most valuable customers.
-
B.
GS
chosen
GS is the vehicle registration code used on license plates for the district of Goslar in Lower Saxony, Germany.
-
C.
GS
GS is the New York Stock Exchange ticker symbol for Goldman Sachs, a leading global investment banking, securities, and asset management firm.
-
D.
GS
GS is the vehicle registration code used on license plates for the town of Gospić in Croatia.
-
E.
GS
GS is the commonly used abbreviation for the School of General Studies, a division of a university that typically offers flexible, interdisciplinary undergraduate programs for nontraditional or returning students.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b6a4348190b9922ed255759078 |
completed | April 10, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e295b3408190a7246115d3ee90e5 |
completed | May 3, 2026, 5:52 a.m. |
Created at: April 9, 2026, 9:09 p.m.