Triple
T11056039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEMSA |
E261378
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | FEMSA Comercio |
E261378
|
NE FINISHED |
How this triple was built (2 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: FEMSA Comercio | Statement: [FEMSA, hasSubsidiary, FEMSA Comercio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FEMSA Comercio Context triple: [FEMSA, hasSubsidiary, FEMSA Comercio]
-
A.
FEMSA
chosen
FEMSA is a large Mexican multinational company best known for its beverage, retail, and logistics operations, including major stakes in Coca-Cola bottling and the OXXO convenience store chain.
-
B.
Coca-Cola FEMSA
Coca-Cola FEMSA is the largest franchise bottler of Coca-Cola products in the world, operating extensive beverage production and distribution networks across Latin America and parts of Asia.
-
C.
Grupo Modelo
Grupo Modelo is a major Mexican brewery best known globally for producing popular beer brands such as Corona.
-
D.
Los Cedros S.A.
Los Cedros S.A. was an Argentine company known for producing the Heinkel Kabine microcar under license.
-
E.
Colbún S.A.
Colbún S.A. is a Chilean electric power company that develops, owns, and operates a portfolio of hydroelectric and thermal power plants.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a152b4819095b74a8996346077 |
completed | April 9, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e74e1dc881908afc01b328cda843 |
completed | April 18, 2026, 8:19 p.m. |
Created at: April 8, 2026, 9:26 p.m.