Triple
T34696920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabbatical Officer |
E891055
|
entity |
| Predicate | isMostCommonInCountry |
P55272
|
FINISHED |
| Object | United Kingdom |
—
|
NE NERFINISHED |
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: United Kingdom | Statement: [Sabbatical Officer, isMostCommonInCountry, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostCommonInCountry Context triple: [Sabbatical Officer, isMostCommonInCountry, United Kingdom]
-
A.
commonInCountry
Indicates that something occurs frequently or is widespread within a specified country.
-
B.
countryOrRegionOfPrevalence
chosen
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
C.
moreCommonIn
Indicates that something occurs with greater frequency or prevalence in one group, context, or location than in another.
-
D.
prevalentIn
Indicates that something occurs frequently or is commonly found within a particular context, group, or environment.
-
E.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 2:05 a.m.