Triple
T19802912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neuhaus an der Pegnitz |
E475731
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | LAU |
—
|
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: LAU | Statement: [Neuhaus an der Pegnitz, vehicleRegistrationCode, LAU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LAU Context triple: [Neuhaus an der Pegnitz, vehicleRegistrationCode, LAU]
-
A.
LAU
chosen
LAU is the vehicle registration code for the German town of Lauf an der Pegnitz in Bavaria.
-
B.
LAU
LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
-
C.
Lau
Lau is an Austronesian language spoken by the Lau people of northeast Malaita in the Solomon Islands.
-
D.
LAJ
LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
-
E.
La La
"La La" is a pop-rock song by American singer Ashlee Simpson from her debut album "Autobiography," known for its edgy lyrics and rebellious tone.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654257cb4819096fb2aa5d1f7fbb0 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.