Triple
T10396807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Endemol Shine Group |
E245041
|
entity |
| Predicate | numberOfCountriesWithOperations |
P93697
|
FINISHED |
| Object | 30+ |
—
|
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: 30+ | Statement: [Endemol Shine Group, numberOfCountriesWithOperations, 30+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCountriesWithOperations Context triple: [Endemol Shine Group, numberOfCountriesWithOperations, 30+]
-
A.
hasNumberOfContinentsWithOperations
Indicates the count of distinct continents in which an entity conducts operations.
-
B.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
C.
numberOperational
Indicates that an entity is currently functioning and available for use in its intended operational capacity.
-
D.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
E.
numberOfCountryOffices
Indicates the total count of offices or branches that an organization maintains across different countries.
- F. None of above. chosen
Provenance (4 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:06 p.m.