Triple
T2506895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bureau International des Expositions |
E52604
|
entity |
| Predicate | setsRule |
P8188
|
FINISHED |
| Object | maximum frequency of World Expos |
—
|
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: maximum frequency of World Expos | Statement: [Bureau International des Expositions, setsRule, maximum frequency of World Expos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsRule Context triple: [Bureau International des Expositions, setsRule, maximum frequency of World Expos]
-
A.
setsRulesFor
chosen
Indicates that one entity establishes or defines rules, guidelines, or constraints that another entity is expected to follow.
-
B.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
C.
eligibilityRulesSetBy
Indicates that one party defines or establishes the criteria or rules determining another party’s eligibility for something.
-
D.
setsBoundary
Indicates that one entity defines or forms the limiting edge or border of another entity.
-
E.
usesRulesFrom
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.