Triple
T16344703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annecy Round |
E396900
|
entity |
| Predicate | hasNumberOfParticipatingCountries |
P2436
|
FINISHED |
| Object | 34 |
—
|
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: 34 | Statement: [Annecy Round, hasNumberOfParticipatingCountries, 34]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfParticipatingCountries Context triple: [Annecy Round, hasNumberOfParticipatingCountries, 34]
-
A.
countryParticipation
Indicates that a country takes part in, is involved with, or contributes to a particular event, activity, agreement, or organization.
-
B.
numberOfParticipatingNations
chosen
Indicates the total count of nations that take part in a specified event, activity, or context.
-
C.
numberOfParticipatingCities
Indicates the total count of cities that take part in a specified event, program, or activity.
-
D.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
E.
hasEuropeanParticipation
Indicates that an entity involves or includes participation from European individuals, organizations, or countries.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da0da1808190b6477613a07c7a88 |
completed | April 18, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69e226eba9b48190af6e80d3d1c2aed3 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.