Triple
T9080374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vechta |
E217603
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | VEC |
E651237
|
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: VEC | Statement: [Vechta, hasVehicleRegistrationCode, VEC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VEC Context triple: [Vechta, hasVehicleRegistrationCode, VEC]
-
A.
VEC
chosen
VEC is the vehicle registration code used on license plates for vehicles registered in the District of Vechta in Lower Saxony, Germany.
-
B.
vec
vec is the ISO 639-3 code for the Venetian language, a Romance language spoken primarily in the Veneto region of Italy and surrounding areas.
-
C.
VECC
VECC is the ICAO airport code for Netaji Subhas Chandra Bose International Airport in Kolkata, India.
-
D.
VES
VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
-
E.
VELO
VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9607942c8190a21620892ce3cbe5 |
completed | April 1, 2026, 3:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffe28ae548190924cc7bbf453f3f3 |
completed | April 3, 2026, 5:51 p.m. |
Created at: March 30, 2026, 7:13 p.m.