Triple
T25834586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baselworld |
E650760
|
entity |
| Predicate | peakExhibitorNumbers |
P143910
|
FINISHED |
| Object | over 1500 exhibitors |
—
|
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 1500 exhibitors | Statement: [Baselworld, peakExhibitorNumbers, over 1500 exhibitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakExhibitorNumbers Context triple: [Baselworld, peakExhibitorNumbers, over 1500 exhibitors]
-
A.
exhibitorsNumber
chosen
Indicates the total count of exhibitors associated with a given event or exhibition.
-
B.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
C.
hasExhibitors
Indicates that an entity includes, hosts, or is associated with one or more exhibitors.
-
D.
exhibitorsFrom
Indicates a relationship where certain exhibitors originate from, are associated with, or come from a specified source, location, or organization.
-
E.
exhibitFor
Indicates a relationship where something is displayed, presented, or shown for the benefit, use, or consideration of a particular audience, purpose, or entity.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f601f485c48190bdbeb260653d9849 |
completed | May 2, 2026, 1:53 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:41 a.m.