Triple
T9684357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glâne District |
E234366
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Promasens
Promasens is a small Swiss municipality located in the canton of Fribourg within the Glâne District.
|
E815280
|
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: Promasens | Statement: [Glâne District, containsMunicipality, Promasens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Promasens Context triple: [Glâne District, containsMunicipality, Promasens]
-
A.
Teckberg
Teckberg is a prominent hill in the Swabian Jura of Baden-Württemberg, Germany, best known as the site of the historic Teck Castle overlooking the surrounding region.
-
B.
Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
-
C.
Omapere
Omapere is a small coastal settlement and holiday destination on the southern shore of Hokianga Harbour in New Zealand’s Northland Region.
-
D.
Oukaimeden
Oukaimeden is a popular ski resort and mountain destination in the High Atlas Mountains of Morocco, known for its winter sports and scenic alpine landscapes.
-
E.
Nakasero
Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
- 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: Promasens Triple: [Glâne District, containsMunicipality, Promasens]
Generated description
Promasens is a small Swiss municipality located in the canton of Fribourg within the Glâne District.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Promasens Target entity description: Promasens is a small Swiss municipality located in the canton of Fribourg within the Glâne District.
-
A.
Teckberg
Teckberg is a prominent hill in the Swabian Jura of Baden-Württemberg, Germany, best known as the site of the historic Teck Castle overlooking the surrounding region.
-
B.
Tamasopo
Tamasopo is a small town in the Huasteca Potosina region of San Luis Potosí, Mexico, known for its lush landscapes and popular nearby waterfalls and natural swimming areas.
-
C.
Omapere
Omapere is a small coastal settlement and holiday destination on the southern shore of Hokianga Harbour in New Zealand’s Northland Region.
-
D.
Oukaimeden
Oukaimeden is a popular ski resort and mountain destination in the High Atlas Mountains of Morocco, known for its winter sports and scenic alpine landscapes.
-
E.
Nakasero
Nakasero is a central and upscale neighborhood in Kampala, Uganda, known for its government offices, embassies, hotels, and commercial centers.
- 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_69ca84c99e34819092e5563a7106cfca |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ccf21a08190a1302b933b9e50be |
completed | April 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19106e67881909505287620d2f781 |
completed | April 4, 2026, 10:30 p.m. |
| NEDg | Description generation | batch_69d19375fd8481909620e8e68d73ec17 |
completed | April 4, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d19416efd48190865d0178e5e893fa |
completed | April 4, 2026, 10:43 p.m. |
Created at: March 30, 2026, 8:16 p.m.