Triple
T11150242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czech Republic–United States relations |
E263764
|
entity |
| Predicate | peopleToPeopleLinksInclude |
P98102
|
FINISHED |
| Object | tourism |
—
|
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: tourism | Statement: [Czech Republic–United States relations, peopleToPeopleLinksInclude, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peopleToPeopleLinksInclude Context triple: [Czech Republic–United States relations, peopleToPeopleLinksInclude, tourism]
-
A.
peopleToPeopleLink
Indicates a relationship that connects one person to another person in some defined way.
-
B.
includesPeopleOf
Indicates that a group, organization, or entity contains or encompasses certain people as its members or participants.
-
C.
peopleAssociatedWith
Indicates that there exists some form of connection, involvement, or relationship between the referenced people.
-
D.
partnerInOrganizationWith
Indicates that two entities are associated as partners within the same organization or organizational context.
-
E.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
| PDg | Predicate description generation | batch_69d7706116248190a87440bec3960884 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:28 p.m.