Triple
T16492143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. President |
E400592
|
entity |
| Predicate | correspondsToTitleInLocalLanguage |
P85853
|
FINISHED |
| Object | Претседател на Република Северна Македонија |
—
|
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: Претседател на Република Северна Македонија | Statement: [Mr. President, correspondsToTitleInLocalLanguage, Претседател на Република Северна Македонија]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToTitleInLocalLanguage Context triple: [Mr. President, correspondsToTitleInLocalLanguage, Претседател на Република Северна Македонија]
-
A.
titleInLocalLanguage
chosen
Indicates that an entity’s title is expressed in the primary or native language of a specified place or community.
-
B.
hasTitleInLanguage
Indicates that an entity has a specific title expressed in a particular language.
-
C.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
D.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
E.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e30cb648190a52cb32896c4ac5a |
completed | April 18, 2026, 7:09 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:13 a.m.