Triple
T1151155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heineken N.V. |
E23679
|
entity |
| Predicate | numberOfCountriesOfOperation |
P3809
|
FINISHED |
| Object | over 70 |
—
|
LITERAL 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: over 70 | Statement: [Heineken N.V., numberOfCountriesOfOperation, over 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesOfOperation Context triple: [Heineken N.V., numberOfCountriesOfOperation, over 70]
-
A.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
B.
hasNumberOfCountries
chosen
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
C.
numberOfParticipatingNations
Indicates the total count of nations that take part in a specified event, activity, or context.
-
D.
numberOfCountryOffices
Indicates the total count of offices or branches that an organization maintains across different countries.
-
E.
operatedInRegion
Indicates that an entity conducted operations or activities within a specified geographic region.
- F. None of above.
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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bd0bed00819091d71983d787a030 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4ee3988190ac89c5ae5b10e316 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.