Triple
T31481741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Brenninkmeijer |
E803162
|
entity |
| Predicate | businessSphere |
P172560
|
FINISHED |
| Object | European retail sector |
—
|
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: European retail sector | Statement: [Albert Brenninkmeijer, businessSphere, European retail sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessSphere Context triple: [Albert Brenninkmeijer, businessSphere, European retail sector]
-
A.
businessScale
Indicates the relative size or level of operations of a business, such as its scope, capacity, or market reach.
-
B.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
-
C.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
D.
businessGroup
Indicates that entities are associated as part of the same business group or organizational unit within a corporate structure.
-
E.
business
Indicates that an entity is engaged in commercial or professional activities, such as providing goods or services for profit.
- 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_69f348c9477c8190bc0a21f6d482d2fc |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ac1ed23c8190ace57ffc9d8a3dc6 |
completed | May 3, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aba8fba48190bc1a17117244cae1 |
completed | May 3, 2026, 1:58 a.m. |
Created at: April 30, 2026, 9:32 p.m.