Triple
T3268275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancy |
E68579
|
entity |
| Predicate | hasRegion |
P285
|
FINISHED |
| Object |
La Praille
La Praille is an urban district in the municipality of Lancy, near Geneva, known for its commercial centers, stadium, and mixed-use developments.
|
E341413
|
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: La Praille | Statement: [Lancy, hasRegion, La Praille]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Praille Context triple: [Lancy, hasRegion, La Praille]
-
A.
Welkenraedt
Welkenraedt is a municipality in the province of Liège in eastern Belgium, near the German border.
-
B.
Gave de Pau
Gave de Pau is a river in southwestern France that flows through the city of Pau and forms part of the Adour river system in the Pyrenees region.
-
C.
Dugommier
Dugommier was a French Revolutionary general noted for his leadership in key campaigns such as the Siege of Toulon and the War of the Pyrenees.
-
D.
Guignard
Guignard was a prominent Brazilian painter and art educator known for his lyrical landscapes and significant influence on modern Brazilian art.
-
E.
Meesseman
Meesseman is the surname of Belgian professional basketball star Emma Meesseman, known for her success in European leagues and the WNBA.
- 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: La Praille Triple: [Lancy, hasRegion, La Praille]
Generated description
La Praille is an urban district in the municipality of Lancy, near Geneva, known for its commercial centers, stadium, and mixed-use developments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Praille Target entity description: La Praille is an urban district in the municipality of Lancy, near Geneva, known for its commercial centers, stadium, and mixed-use developments.
-
A.
Welkenraedt
Welkenraedt is a municipality in the province of Liège in eastern Belgium, near the German border.
-
B.
Gave de Pau
Gave de Pau is a river in southwestern France that flows through the city of Pau and forms part of the Adour river system in the Pyrenees region.
-
C.
Dugommier
Dugommier was a French Revolutionary general noted for his leadership in key campaigns such as the Siege of Toulon and the War of the Pyrenees.
-
D.
Guignard
Guignard was a prominent Brazilian painter and art educator known for his lyrical landscapes and significant influence on modern Brazilian art.
-
E.
Meesseman
Meesseman is the surname of Belgian professional basketball star Emma Meesseman, known for her success in European leagues and the WNBA.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcf9c6c819092f9c618b778b46d |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b28ef261ec819091c62620765e2cef |
completed | March 12, 2026, 10:01 a.m. |
| NEDg | Description generation | batch_69b28f9efe408190bcb1e16931b2fe62 |
completed | March 12, 2026, 10:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2a8b873b081909bbb5de329e45169 |
completed | March 12, 2026, 11:51 a.m. |
Created at: March 8, 2026, 3:09 p.m.