Triple
T7202678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Library Association |
E148585
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CLA
CLA is a former national professional organization that represented and supported libraries and library workers across Canada.
|
E649061
|
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: CLA | Statement: [Canadian Library Association, abbreviation, CLA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLA Context triple: [Canadian Library Association, abbreviation, CLA]
-
A.
CLA
The Mercedes-Benz CLA is a compact luxury four-door coupé known for its sleek styling, advanced technology, and entry-level positioning within the brand’s lineup.
-
B.
CLS
The Mercedes-Benz CLS is a luxury four-door coupé known for pioneering the modern coupé-sedan design with sleek styling and high-end performance.
-
C.
CLS
CLS is a set of rules in the .NET framework that defines a subset of common language features to ensure interoperability among different .NET languages.
-
D.
CCA
CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
-
E.
CCA
CCA is the ICAO airline designator used to identify Air China in international aviation operations.
- 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: CLA Triple: [Canadian Library Association, abbreviation, CLA]
Generated description
CLA is a former national professional organization that represented and supported libraries and library workers across Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CLA Target entity description: CLA is a former national professional organization that represented and supported libraries and library workers across Canada.
-
A.
CLA
The Mercedes-Benz CLA is a compact luxury four-door coupé known for its sleek styling, advanced technology, and entry-level positioning within the brand’s lineup.
-
B.
CLS
The Mercedes-Benz CLS is a luxury four-door coupé known for pioneering the modern coupé-sedan design with sleek styling and high-end performance.
-
C.
CLS
CLS is a set of rules in the .NET framework that defines a subset of common language features to ensure interoperability among different .NET languages.
-
D.
CCA
CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
-
E.
CCA
CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfb5e27c8190867fb4968dea2e4e |
completed | March 28, 2026, 11:47 a.m. |
| NEDg | Description generation | batch_69c7c0e45cc48190bea1daf65e5650b3 |
completed | March 28, 2026, 11:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7c13e64208190ba76f5c6a0df40db |
completed | March 28, 2026, 11:53 a.m. |
Created at: March 27, 2026, 2:52 p.m.