Triple
T3199909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emirates |
E67024
|
entity |
| Predicate | numberOfCountriesServed |
P3809
|
FINISHED |
| Object | over 80 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 80 countries | Statement: [Emirates, numberOfCountriesServed, over 80 countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesServed Context triple: [Emirates, numberOfCountriesServed, over 80 countries]
-
A.
hasCountryServed
Indicates that a person or organization has provided service to, or performed duties on behalf of, a specified country.
-
B.
hasNumberOfCountries
chosen
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
C.
capitalOfCountryServed
Indicates that a city serves as the capital of a given country.
-
D.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
E.
servesDestinationCount
Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9ad4b1c8190bc6ad0f025f238c8 |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.