Triple
T19468727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilhelm Dörpfeld |
E487065
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Barmen |
—
|
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: Barmen | Statement: [Wilhelm Dörpfeld, birthPlace, Barmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barmen Context triple: [Wilhelm Dörpfeld, birthPlace, Barmen]
-
A.
Barmen
chosen
Barmen is a historic industrial district in the German city of Wuppertal, known as a former textile and manufacturing center in the Ruhr region.
-
B.
Brannenburg
Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
-
C.
Bornheim
Bornheim is a lively residential and nightlife district in Frankfurt am Main, Germany, known for its traditional cider taverns, historic streets, and vibrant local culture.
-
D.
Barmer
Barmer is a prominent city in the western Indian state of Rajasthan, known for its desert landscape, handicrafts, and proximity to the Thar Desert.
-
E.
Borken
Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e4b230819097c8804ee91988ea |
completed | April 20, 2026, 2:10 p.m. |
Created at: April 10, 2026, 1:39 p.m.