Triple
T16482419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidiland |
E400352
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
Weesen
Weesen is a picturesque Swiss lakeside town in the Heidiland holiday region, known for its scenic setting on Lake Walen and access to nearby mountains and outdoor activities.
|
E1216196
|
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: Weesen | Statement: [Heidiland, hasAttraction, Weesen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weesen Context triple: [Heidiland, hasAttraction, Weesen]
-
A.
Wusse
Wusse is a small settlement in the German state of Mecklenburg-Vorpommern that serves as the administrative seat of the municipality of Ummanz.
-
B.
Veeweyde
Veeweyde is a neighborhood-level district within the Brussels municipality of Anderlecht, known primarily as a residential area served by the Veeweyde metro station.
-
C.
Heezen
Heezen is a surname most notably associated with American geologist and oceanographer Bruce C. Heezen, a pioneer in mapping the ocean floor.
-
D.
Weeting
Weeting is a small village and civil parish located near the Norfolk-Suffolk border in eastern England.
-
E.
Weenen
Weenen is a small historic town in KwaZulu-Natal, South Africa, known for its agricultural surroundings and proximity to the Weenen Game Reserve.
- 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: Weesen Triple: [Heidiland, hasAttraction, Weesen]
Generated description
Weesen is a picturesque Swiss lakeside town in the Heidiland holiday region, known for its scenic setting on Lake Walen and access to nearby mountains and outdoor activities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weesen Target entity description: Weesen is a picturesque Swiss lakeside town in the Heidiland holiday region, known for its scenic setting on Lake Walen and access to nearby mountains and outdoor activities.
-
A.
Wusse
Wusse is a small settlement in the German state of Mecklenburg-Vorpommern that serves as the administrative seat of the municipality of Ummanz.
-
B.
Veeweyde
Veeweyde is a neighborhood-level district within the Brussels municipality of Anderlecht, known primarily as a residential area served by the Veeweyde metro station.
-
C.
Heezen
Heezen is a surname most notably associated with American geologist and oceanographer Bruce C. Heezen, a pioneer in mapping the ocean floor.
-
D.
Weeting
Weeting is a small village and civil parish located near the Norfolk-Suffolk border in eastern England.
-
E.
Weenen
Weenen is a small historic town in KwaZulu-Natal, South Africa, known for its agricultural surroundings and proximity to the Weenen Game Reserve.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e03643881908b16ddb9004af5d0 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a005820790c819088d953eeea09328d |
completed | May 10, 2026, 10:04 a.m. |
| NEDg | Description generation | batch_6a0059126e588190b531c145f3c155b4 |
completed | May 10, 2026, 10:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0059bf355c81909d6796482fe7f3e3 |
completed | May 10, 2026, 10:11 a.m. |
Created at: April 10, 2026, 5:13 a.m.