Triple
T15634694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agger |
E375909
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Lohmar |
E688098
|
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: Lohmar | Statement: [Agger, flowsThrough, Lohmar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lohmar Context triple: [Agger, flowsThrough, Lohmar]
-
A.
Lohmar
chosen
Lohmar is a town in the Rhein-Sieg district of North Rhine-Westphalia, Germany, situated near Cologne and known for its green surroundings and residential character.
-
B.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
-
C.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
-
D.
Fritzlar
Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
-
E.
Burscheid
Burscheid is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its mix of rural character and local industry.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb8b4c48190b80fea6877483089 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f372f7c8190ba04b8bd13bff95c |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 4:14 a.m.