Triple
T9684356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glâne District |
E234366
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Lussy
Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
|
E827380
|
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: Lussy | Statement: [Glâne District, containsMunicipality, Lussy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lussy Context triple: [Glâne District, containsMunicipality, Lussy]
-
A.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
B.
Chassieu
Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
-
C.
Chasseral
Chasseral is a prominent mountain in the Jura range of western Switzerland, known for its panoramic views and telecommunications installations.
-
D.
Cugny
Cugny is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
-
E.
Peisey-Vallandry
Peisey-Vallandry is a French Alpine ski resort and traditional mountain village area in the Savoie region, known for its access to the Paradiski ski domain.
- 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: Lussy Triple: [Glâne District, containsMunicipality, Lussy]
Generated description
Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lussy Target entity description: Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
-
A.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
B.
Chassieu
Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
-
C.
Chasseral
Chasseral is a prominent mountain in the Jura range of western Switzerland, known for its panoramic views and telecommunications installations.
-
D.
Cugny
Cugny is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
-
E.
Peisey-Vallandry
Peisey-Vallandry is a French Alpine ski resort and traditional mountain village area in the Savoie region, known for its access to the Paradiski ski domain.
- 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_69d1eab6ae348190b1ff4eb10081c5a0 |
completed | April 5, 2026, 4:53 a.m. |
| NEDg | Description generation | batch_69d1ebec25508190ac4c0adb629f79b0 |
completed | April 5, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ec65d5e881909e4caa180b0f8867 |
completed | April 5, 2026, 5 a.m. |
Created at: March 30, 2026, 8:16 p.m.