Triple
T726472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A 49 motorway |
E14735
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | North Hesse |
E108856
|
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: North Hesse | Statement: [A 49 motorway, locatedIn, North Hesse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North Hesse Context triple: [A 49 motorway, locatedIn, North Hesse]
-
A.
North Hesse
chosen
North Hesse is a region in the northern part of the German state of Hesse, centered around the city of Kassel and known for its forests, hills, and cultural heritage.
-
B.
Hesse
Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
-
C.
Sachse
Sachse is a suburban city in the Dallas–Fort Worth metropolitan area of northeastern Texas.
-
D.
South Hesse
South Hesse is a region in the southern part of the German state of Hesse that includes major urban and economic centers such as Darmstadt and the Rhine-Main area.
-
E.
Middle Hesse
Middle Hesse is a central region of the German state of Hesse known for its mix of historic university towns, industrial centers, and rural landscapes.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a9adf08190bf2baade7e2e1c1c |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3b9557cc8190be3137aabdd36216 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:37 p.m.