Triple
T7464367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leer (district) |
E176335
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | LER |
E627972
|
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: LER | Statement: [Leer (district), vehicleRegistrationCode, LER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LER Context triple: [Leer (district), vehicleRegistrationCode, LER]
-
A.
LER
chosen
LER is the vehicle registration code assigned to the German island municipality of Borkum.
-
B.
LR
LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
-
C.
LR
LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
-
D.
LEM
LEM is the original abbreviation for the Apollo Lunar Module, the spacecraft used by NASA astronauts to land on and ascend from the Moon during the Apollo missions.
-
E.
Le
Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d9d25c819087efc772b5b127fa |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8346adb3081908f049d8dcd623215 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:40 p.m.