Triple
T12747898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Year’s Concert |
E304652
|
entity |
| Predicate | approximateCountries |
P98679
|
FINISHED |
| Object | over 90 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 90 countries | Statement: [New Year’s Concert, approximateCountries, over 90 countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateCountries Context triple: [New Year’s Concert, approximateCountries, over 90 countries]
-
A.
collectionCountry
Indicates the country in which an item, specimen, or data was collected.
-
B.
coveredCountry
chosen
Indicates that one entity includes or provides coverage for the territory or jurisdiction of a specified country.
-
C.
country2
Indicates a secondary or alternative country associated with an entity, such as a second nationality, location, or jurisdiction.
-
D.
countryFound
Indicates that a particular country is the location where an entity was discovered, established, or first identified.
-
E.
deltaCountry
Indicates a change or difference in country between two related entities or states.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:27 p.m.