Triple
T8779182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conseil scolaire Viamonde |
E208678
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CSV
Conseil scolaire Viamonde (CSV) is a French-language public secular school board serving students in various regions of Ontario, Canada.
|
E757088
|
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: CSV | Statement: [Conseil scolaire Viamonde, abbreviation, CSV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CSV Context triple: [Conseil scolaire Viamonde, abbreviation, CSV]
-
A.
CSV
CSV (Comma-Separated Values) is a simple, text-based file format commonly used to store and exchange tabular data between different software applications and systems.
-
B.
RFC 4180
RFC 4180 is the Internet standard that formally specifies the common format and rules for Comma-Separated Values (CSV) files.
-
C.
RCFile
RCFile is a columnar storage file format designed for efficient data processing and querying in Hadoop-based systems.
-
D.
Cif
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
-
E.
Excel
Excel is a widely used spreadsheet software by Microsoft that enables data organization, analysis, visualization, and basic to advanced analytics through formulas, functions, and tools like PivotTables.
- 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: CSV Triple: [Conseil scolaire Viamonde, abbreviation, CSV]
Generated description
Conseil scolaire Viamonde (CSV) is a French-language public secular school board serving students in various regions of Ontario, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CSV Target entity description: Conseil scolaire Viamonde (CSV) is a French-language public secular school board serving students in various regions of Ontario, Canada.
-
A.
CSV
CSV (Comma-Separated Values) is a simple, text-based file format commonly used to store and exchange tabular data between different software applications and systems.
-
B.
RFC 4180
RFC 4180 is the Internet standard that formally specifies the common format and rules for Comma-Separated Values (CSV) files.
-
C.
RCFile
RCFile is a columnar storage file format designed for efficient data processing and querying in Hadoop-based systems.
-
D.
Cif
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
-
E.
Excel
Excel is a widely used spreadsheet software by Microsoft that enables data organization, analysis, visualization, and basic to advanced analytics through formulas, functions, and tools like PivotTables.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f531bd481909d877dadf9b6e9fb |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51d69af481909245ca327f36e9c2 |
completed | April 3, 2026, 5:36 a.m. |
| NEDg | Description generation | batch_69cf545edf648190bb7d79a75cd9ba99 |
completed | April 3, 2026, 5:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf5513f894819087a2c39142d597b4 |
completed | April 3, 2026, 5:50 a.m. |
Created at: March 30, 2026, 6:42 p.m.