Triple
T26072511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TEFAF Maastricht |
E657586
|
entity |
| Predicate | hasNumberOfVisitors |
P427
|
FINISHED |
| Object | tens of thousands |
—
|
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: tens of thousands | Statement: [TEFAF Maastricht, hasNumberOfVisitors, tens of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfVisitors Context triple: [TEFAF Maastricht, hasNumberOfVisitors, tens of thousands]
-
A.
hasVisitorNumber
Indicates the assigned sequential number or position of a visitor within a series of visitors to an entity.
-
B.
hasVisitorsFrom
Indicates that an entity receives or has received visitors originating from another specified entity or location.
-
C.
visitorCount
chosen
Indicates the number of visitors associated with a particular entity, context, or time period.
-
D.
hasTargetVisitors
Indicates that something is intended or designed to be visited by a specific group of people as its primary audience or users.
-
E.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
- 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_69ee5bbe539081909efc7f9dd7c1b53c |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 26, 2026, 7:30 p.m.