Triple
T19770435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saputo Inc. |
E474869
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
SAP
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
|
E35622
|
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: SAP | Statement: [Saputo Inc., tickerSymbol, SAP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SAP Context triple: [Saputo Inc., tickerSymbol, SAP]
-
A.
SAP
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
-
B.
SAP
SAP is the commonly used abbreviation for the Société d’Anthropologie de Paris, a French learned society dedicated to the study of anthropology.
-
C.
SAP
SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
-
D.
SAP
SAP is Sweden’s major center-left political party, historically associated with social democracy, the welfare state, and long periods of governing the country.
-
E.
SAP
SAP is the IATA airport code for Ramón Villeda Morales International Airport, the main air gateway serving San Pedro Sula, Honduras.
- 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: SAP Triple: [Saputo Inc., tickerSymbol, SAP]
Generated description
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SAP Target entity description: SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
-
A.
SAP
chosen
SAP is a leading global enterprise software company best known for its ERP solutions that help organizations manage business operations and customer relations.
-
B.
SAP
SAP is the commonly used abbreviation for the Société d’Anthropologie de Paris, a French learned society dedicated to the study of anthropology.
-
C.
SAP
SAP is Sweden’s major center-left political party, historically associated with social democracy, the welfare state, and long periods of governing the country.
-
D.
SAP
SAP is the station code for Lisbon Santa Apolónia, one of the main railway terminals in Lisbon, Portugal.
-
E.
SAP
SAP was the former official currency of South Africa, used before the adoption of the South African rand.
- F. None of above.
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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535ab298819085263dc37cc898cb |
completed | April 20, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07bd74937081908b81d144aa89c5f3 |
completed | May 16, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_6a07be450e608190a008095b0502b2d3 |
completed | May 16, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07bed4c8d8819094fafce7eee69ee7 |
completed | May 16, 2026, 12:48 a.m. |
Created at: April 10, 2026, 1:48 p.m.