Triple
T22789333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallenberg |
E564064
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Liesen
Liesen is a small village in the Hochsauerland region of North Rhine-Westphalia, Germany, known for its rural setting and proximity to the town of Hallenberg.
|
E1554634
|
NE FINISHED |
How this triple was built (4 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: Liesen | Statement: [Hallenberg, locatedNear, Liesen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liesen Context triple: [Hallenberg, locatedNear, Liesen]
-
A.
Leissigen
Leissigen is a Swiss village in the canton of Bern, known for its scenic location in the Bernese Oberland on the shores of Lake Thun.
-
B.
Líšina
Líšina is a small village in the Plzeň Region of the Czech Republic, situated within the administrative area of the Plzeň-South District.
-
C.
Liepe
Liepe is a small municipality in the district of Barnim in the German state of Brandenburg.
-
D.
Vohenstrauß
Vohenstrauß is a small town in the Upper Palatinate region of Bavaria, Germany, known for its historic architecture and surrounding forested landscapes.
-
E.
Rechlin
Rechlin is a small municipality in northeastern Germany’s Mecklenburg Lake District, known as a gateway to Müritz National Park and the surrounding lake landscape.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Liesen Triple: [Hallenberg, locatedNear, Liesen]
Generated description
Liesen is a small village in the Hochsauerland region of North Rhine-Westphalia, Germany, known for its rural setting and proximity to the town of Hallenberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liesen Target entity description: Liesen is a small village in the Hochsauerland region of North Rhine-Westphalia, Germany, known for its rural setting and proximity to the town of Hallenberg.
-
A.
Leissigen
Leissigen is a Swiss village in the canton of Bern, known for its scenic location in the Bernese Oberland on the shores of Lake Thun.
-
B.
Líšina
Líšina is a small village in the Plzeň Region of the Czech Republic, situated within the administrative area of the Plzeň-South District.
-
C.
Liepe
Liepe is a small municipality in the district of Barnim in the German state of Brandenburg.
-
D.
Vohenstrauß
Vohenstrauß is a small town in the Upper Palatinate region of Bavaria, Germany, known for its historic architecture and surrounding forested landscapes.
-
E.
Rechlin
Rechlin is a small municipality in northeastern Germany’s Mecklenburg Lake District, known as a gateway to Müritz National Park and the surrounding lake landscape.
- F. None of above. chosen
Provenance (5 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c3488708190812f7d2edac92184 |
completed | April 29, 2026, 3:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b9e905b148190b319d88ca3e7ca8e |
completed | May 18, 2026, 11:19 p.m. |
| NEDg | Description generation | batch_6a0b9f0e73048190ac2e1ad53912dde5 |
completed | May 18, 2026, 11:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b9ff292b88190b1f318a8a801fbd1 |
completed | May 18, 2026, 11:25 p.m. |
Created at: April 17, 2026, 3:29 p.m.