Triple
T20684108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centennial Exposition |
E508368
|
entity |
| Predicate | numberOfParticipatingCountriesApproximate |
P2436
|
FINISHED |
| Object | over 30 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: over 30 countries | Statement: [Centennial Exposition, numberOfParticipatingCountriesApproximate, over 30 countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfParticipatingCountriesApproximate Context triple: [Centennial Exposition, numberOfParticipatingCountriesApproximate, over 30 countries]
-
A.
numberOfParticipatingNations
chosen
Indicates the total count of nations that take part in a specified event, activity, or context.
-
B.
numberOfParticipatingCities
Indicates the total count of cities that take part in a specified event, program, or activity.
-
C.
countryParticipation
Indicates that a country takes part in, is involved with, or contributes to a particular event, activity, agreement, or organization.
-
D.
formerParticipatingCountry
Indicates that a country previously took part in a specific organization, event, or arrangement but is no longer a participating member.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6beaae5608190ac8cc64aa4717d53 |
completed | April 21, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:45 a.m.