Triple
T7891819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AB InBev |
E183252
|
entity |
| Predicate | hasNumberOfContinentsWithOperations |
P79596
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [AB InBev, hasNumberOfContinentsWithOperations, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfContinentsWithOperations Context triple: [AB InBev, hasNumberOfContinentsWithOperations, 6]
-
A.
operatesToContinents
Indicates that an entity conducts or provides operations or services that extend across or are directed toward multiple continents.
-
B.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
C.
hasLandOperations
Indicates that an entity conducts or is responsible for activities, services, or operations carried out on land.
-
D.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
-
E.
hasNumberOfInhabitedIslands
Indicates the relationship that specifies how many islands within a given area or jurisdiction are inhabited.
- F. None of above. chosen
Provenance (4 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39fef2e48190a6282c217c33c57a |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 5 p.m.