Triple
T20729926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freudenstadt (district) |
E509545
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | FDS |
—
|
NE NERFINISHED |
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: FDS | Statement: [Freudenstadt (district), vehicleRegistrationCode, FDS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FDS Context triple: [Freudenstadt (district), vehicleRegistrationCode, FDS]
-
A.
FDS
FDS is the onboard computer system on NASA’s Voyager 1 spacecraft responsible for managing instruments and formatting data for transmission back to Earth.
-
B.
FDS
chosen
FDS is the vehicle registration code for the district of Freudenstadt in the German state of Baden-Württemberg.
-
C.
FDS
FDS is a floppy disk-based add-on for Nintendo’s Famicom console that enabled expanded game storage and features in the mid-1980s.
-
D.
FDS
FDS is a prestigious postgraduate professional qualification in dentistry awarded by certain Royal Colleges and dental institutions.
-
E.
FDSK
FDSK is the ICAO airport code for King Mswati III International Airport, the main international gateway to Eswatini.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ec9820819093a07f90503686b2 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:30 p.m.