Triple
T5392676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dornach |
E120369
|
entity |
| Predicate | sharesBorderWith |
P224
|
FINISHED |
| Object |
Arlesheim
Arlesheim is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its historic cathedral and picturesque setting near Basel.
|
E523826
|
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: Arlesheim | Statement: [Dornach, sharesBorderWith, Arlesheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arlesheim Context triple: [Dornach, sharesBorderWith, Arlesheim]
-
A.
Adorp
Adorp is a small village in the municipality of Het Hogeland in the province of Groningen in the northern Netherlands.
-
B.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
C.
Schafhausen
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
D.
Hermance
Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern Switzerland.
-
E.
Grenchen
Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
- 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: Arlesheim Triple: [Dornach, sharesBorderWith, Arlesheim]
Generated description
Arlesheim is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its historic cathedral and picturesque setting near Basel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arlesheim Target entity description: Arlesheim is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, known for its historic cathedral and picturesque setting near Basel.
-
A.
Adorp
Adorp is a small village in the municipality of Het Hogeland in the province of Groningen in the northern Netherlands.
-
B.
Adliswil
Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
-
C.
Schafhausen
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
-
D.
Hermance
Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern Switzerland.
-
E.
Grenchen
Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd8719ff04819089e3a90f90b5e3fc |
completed | March 20, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf6c4cdec48190908b52a37b82c2d1 |
completed | March 22, 2026, 4:13 a.m. |
| NEDg | Description generation | batch_69bf6d329cf08190bb2927602c6bb721 |
completed | March 22, 2026, 4:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf6d938dec81909895bcc6a4947d37 |
completed | March 22, 2026, 4:18 a.m. |
Created at: March 20, 2026, 2:04 p.m.