Triple
T4490206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valdigne |
E107352
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
La Salle
La Salle is a small alpine municipality in Italy’s Aosta Valley, known for its scenic mountain landscapes and proximity to Mont Blanc.
|
E446747
|
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 Salle | Statement: [Valdigne, contains, La Salle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Salle Context triple: [Valdigne, contains, La Salle]
-
A.
La Salle College
La Salle College is a prestigious boys' secondary school in Hong Kong known for its strong academic performance and prominent alumni in politics, business, and public service.
-
B.
Regis
Regis is an honorific term historically used in English to denote royal association, particularly in place names granted royal patronage.
-
C.
Loyola
Loyola is a Spanish Basque noble family name most famously associated with Ignatius of Loyola, the founder of the Society of Jesus (Jesuits).
-
D.
Salud-La Salle
Salud-La Salle is a district of Santa Cruz de Tenerife on the island of Tenerife in Spain’s Canary Islands.
-
E.
Collège Bourbon
Collège Bourbon was a prestigious secondary school in Aix-en-Provence, France, known for educating notable 19th-century figures such as the writer Émile Zola.
- 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 Salle Triple: [Valdigne, contains, La Salle]
Generated description
La Salle is a small alpine municipality in Italy’s Aosta Valley, known for its scenic mountain landscapes and proximity to Mont Blanc.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Salle Target entity description: La Salle is a small alpine municipality in Italy’s Aosta Valley, known for its scenic mountain landscapes and proximity to Mont Blanc.
-
A.
La Salle College
La Salle College is a prestigious boys' secondary school in Hong Kong known for its strong academic performance and prominent alumni in politics, business, and public service.
-
B.
Regis
Regis is an honorific term historically used in English to denote royal association, particularly in place names granted royal patronage.
-
C.
Loyola
Loyola is a Spanish Basque noble family name most famously associated with Ignatius of Loyola, the founder of the Society of Jesus (Jesuits).
-
D.
Salud-La Salle
Salud-La Salle is a district of Santa Cruz de Tenerife on the island of Tenerife in Spain’s Canary Islands.
-
E.
Collège Bourbon
Collège Bourbon was a prestigious secondary school in Aix-en-Provence, France, known for educating notable 19th-century figures such as the writer Émile Zola.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd67aee5908190888efb94eee725e5 |
completed | March 20, 2026, 3:28 p.m. |
| NEDg | Description generation | batch_69bd6c62f40881909e30291317ab5f99 |
completed | March 20, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bd6cf9a04881909a25ce291df748a0 |
completed | March 20, 2026, 3:51 p.m. |
Created at: March 20, 2026, 12:59 p.m.