Triple
T13227665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bertha Benz |
E314922
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Ladenburg |
E314920
|
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: Ladenburg | Statement: [Bertha Benz, residence, Ladenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ladenburg Context triple: [Bertha Benz, residence, Ladenburg]
-
A.
Ladenburg
chosen
Ladenburg is a historic town in southwestern Germany known for its well-preserved old town and its association with automobile pioneer Karl Benz.
-
B.
Löwenthal
Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
-
C.
Friedberg
Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
-
D.
Berkheim
Berkheim is a small municipality in the district of Biberach in the federal state of Baden-Württemberg in southern Germany.
-
E.
Hollstadt
Hollstadt is a small municipality in the Bavarian district of Rhön-Grabfeld in northern Germany.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3407388190bef886884cb75912 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:21 p.m.