Triple
T23452797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lippstadt |
E567830
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | river Lippe |
—
|
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: river Lippe | Statement: [Lippstadt, locatedOn, river Lippe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: river Lippe Context triple: [Lippstadt, locatedOn, river Lippe]
-
A.
Lippe
Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
-
B.
Lippe
chosen
The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
-
C.
river Sieg
The river Sieg is a tributary of the Rhine in western Germany, flowing through North Rhine-Westphalia and Rhineland-Palatinate and giving its name to several nearby towns.
-
D.
Schwalm River
The Schwalm River is a waterway in the German state of Hesse that lends its name to the surrounding Schwalm-Eder region.
-
E.
river Giessen
The river Giessen is a small watercourse in the Dutch province of South Holland that flows through rural polder landscapes and has historically influenced the development and naming of nearby municipalities.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a694f19081909117bc9b10ca8a83 |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:52 p.m.