Triple
T3700339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sihl River |
E78561
|
entity |
| Predicate | crosses |
P416
|
FINISHED |
| Object |
Sihlwald
Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
|
E381042
|
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: Sihlwald | Statement: [Sihl River, crosses, Sihlwald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sihlwald Context triple: [Sihl River, crosses, Sihlwald]
-
A.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
B.
Zürichhorn
Zürichhorn is a popular lakeside park and recreational area in Zurich known for its green spaces, lakeshore promenade, and cultural attractions.
-
C.
Aarberg
Aarberg is a small historic town in the canton of Bern in Switzerland, known for its medieval center and distinctive wooden bridge over the Aare River.
-
D.
Oberegg
Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
-
E.
Thun
Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
- 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: Sihlwald Triple: [Sihl River, crosses, Sihlwald]
Generated description
Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sihlwald Target entity description: Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
-
A.
Bettlach
Bettlach is a Swiss municipality located in the canton of Solothurn.
-
B.
Zürichhorn
Zürichhorn is a popular lakeside park and recreational area in Zurich known for its green spaces, lakeshore promenade, and cultural attractions.
-
C.
Aarberg
Aarberg is a small historic town in the canton of Bern in Switzerland, known for its medieval center and distinctive wooden bridge over the Aare River.
-
D.
Oberegg
Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
-
E.
Thun
Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc514eb6c8190b3b74a603c717729 |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3df86bc819088db92eecee69fd3 |
completed | March 14, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69b4c7e579d4819090edfa8a858c40c4 |
completed | March 14, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c86511e48190872b3d85019bc013 |
completed | March 14, 2026, 2:31 a.m. |
Created at: March 8, 2026, 3:26 p.m.