Triple
T7252337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Manufacturing Technology Show |
E157632
|
entity |
| Predicate | hasVisitorsFrom |
P75569
|
FINISHED |
| Object | multiple countries |
—
|
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: multiple countries | Statement: [International Manufacturing Technology Show, hasVisitorsFrom, multiple countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisitorsFrom Context triple: [International Manufacturing Technology Show, hasVisitorsFrom, multiple countries]
-
A.
hasVisitation
Indicates that one entity visits, or is allowed or scheduled to visit, another entity or location.
-
B.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
C.
primaryVisitors
Indicates that certain entities are the main or most important visitors associated with another entity or context.
-
D.
hasVisitorType
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
-
E.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea7ae0e48190bd80c91bad1976c6 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e889854481908c765ce2107f2d3a |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 27, 2026, 2:56 p.m.