Triple
T14459590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabinet Secretary |
E358545
|
entity |
| Predicate | variesByCountry |
P20589
|
FINISHED |
| Object | title |
—
|
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: title | Statement: [Cabinet Secretary, variesByCountry, title]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: variesByCountry Context triple: [Cabinet Secretary, variesByCountry, title]
-
A.
rateVariesBy
Indicates that the rate of something changes depending on a specified factor, condition, or category.
-
B.
termVariesBy
Indicates that the value or meaning of a term changes depending on a specified factor, such as context, dimension, or condition.
-
C.
countryVariant
Indicates that one entity is a country-specific variant or localized version of another entity.
-
D.
usageVariesBy
Indicates that the way something is used differs depending on a specified factor, such as context, user, location, or conditions.
-
E.
observanceMayVaryByCountry
chosen
Indicates that the way something is observed, celebrated, or practiced can differ depending on the 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91aabebc819097eb61b2d81c9a91 |
completed | April 14, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.