Triple
T23284967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheinwaldhorn |
E588960
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Rheinwald |
—
|
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: Rheinwald | Statement: [Rheinwaldhorn, locatedNear, Rheinwald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rheinwald Context triple: [Rheinwaldhorn, locatedNear, Rheinwald]
-
A.
Rheinwald
chosen
Rheinwald is a remote alpine valley region in southeastern Switzerland known for its dramatic mountain scenery and traditional villages.
-
B.
Rheindahlen
Rheindahlen is a district of Mönchengladbach in western Germany that became well known as a major British military garrison and administrative center during the Cold War.
-
C.
Schildwolde
Schildwolde is a village in the Dutch province of Groningen, known for its historic church and rural character within the municipality of Midden-Groningen.
-
D.
Heuckewalde
Heuckewalde is a small municipality in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan region.
-
E.
Kellerwald
Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1964600888190b40ecbefdc8aec64 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 4:59 p.m.