Triple
T12669073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LeVar Burton |
E302629
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Landstuhl |
E589460
|
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: Landstuhl | Statement: [LeVar Burton, placeOfBirth, Landstuhl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landstuhl Context triple: [LeVar Burton, placeOfBirth, Landstuhl]
-
A.
Landstuhl
chosen
Landstuhl is a small town in southwestern Germany, known for its proximity to the U.S. military’s Ramstein Air Base and its historic Nanstein Castle.
-
B.
Lorze
The Lorze is a river in central Switzerland that drains Lake Zug and flows through the cantons of Zug and Aargau before joining the Reuss.
-
C.
Carle
Carle is a given name most notably borne by the 18th-century French painter Carle Van Loo, a prominent figure in the Rococo art movement.
-
D.
Midewin
Midewin is an alternative name for the Midewiwin, a traditional Anishinaabe spiritual society known for its healing practices and ceremonial teachings.
-
E.
Grafenwöhr
Grafenwöhr is a Bavarian town best known for hosting one of the largest U.S. Army training areas in Europe.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96183a6048190b2ef219eb9d20aa4 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688e101481909bc3b9e13ed84632 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:20 p.m.