Triple
T11056035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FEMSA |
E261378
|
entity |
| Predicate | tickerSymbol |
P1447
|
FINISHED |
| Object |
FMX
FMX is the stock ticker symbol for Fomento Económico Mexicano, S.A.B. de C.V. (FEMSA), a major Mexican multinational beverage and retail company.
|
E902700
|
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: FMX | Statement: [FEMSA, tickerSymbol, FMX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FMX Context triple: [FEMSA, tickerSymbol, FMX]
-
A.
FMX
FMX (FireMonkey) is a cross-platform application development framework used in Delphi for building native GUI applications on Windows, macOS, iOS, and Android.
-
B.
FXM
FXM is an American cable television channel owned by FX Networks that primarily airs movies, including contemporary films and classic titles.
-
C.
FMU
FMU is a public university in Florence, South Carolina, known for its liberal arts and professional programs.
-
D.
FX2
FX2 is a 1991 action-thriller film and sequel to the movie "F/X," starring Brian Dennehy and Bryan Brown as they again use movie special-effects skills to outwit criminals.
-
E.
FMS
FMS is the post-nominal abbreviation used by members of the Marist Brothers, a Catholic religious institute dedicated to education and youth work.
- 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: FMX Triple: [FEMSA, tickerSymbol, FMX]
Generated description
FMX is the stock ticker symbol for Fomento Económico Mexicano, S.A.B. de C.V. (FEMSA), a major Mexican multinational beverage and retail company.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FMX Target entity description: FMX is the stock ticker symbol for Fomento Económico Mexicano, S.A.B. de C.V. (FEMSA), a major Mexican multinational beverage and retail company.
-
A.
FMX
FMX (FireMonkey) is a cross-platform application development framework used in Delphi for building native GUI applications on Windows, macOS, iOS, and Android.
-
B.
FXM
FXM is an American cable television channel owned by FX Networks that primarily airs movies, including contemporary films and classic titles.
-
C.
FMU
FMU is a public university in Florence, South Carolina, known for its liberal arts and professional programs.
-
D.
FX2
FX2 is a 1991 action-thriller film and sequel to the movie "F/X," starring Brian Dennehy and Bryan Brown as they again use movie special-effects skills to outwit criminals.
-
E.
FMS
FMS is the post-nominal abbreviation used by members of the Marist Brothers, a Catholic religious institute dedicated to education and youth work.
- 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_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_69e3c86e0e6481908f091497313132c1 |
completed | April 18, 2026, 6:07 p.m. |
| NEDg | Description generation | batch_69e3cefc00148190a1850dc6e31523c3 |
completed | April 18, 2026, 6:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3d014a644819092c76aa02b573ca9 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 8, 2026, 9:26 p.m.