Triple
T7997924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor-General of Lithuania |
E186173
|
entity |
| Predicate | officeHolderTitleInRussian |
P80251
|
FINISHED |
| Object | генерал-губернатор литовский |
—
|
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: генерал-губернатор литовский | Statement: [Governor-General of Lithuania, officeHolderTitleInRussian, генерал-губернатор литовский]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTitleInRussian Context triple: [Governor-General of Lithuania, officeHolderTitleInRussian, генерал-губернатор литовский]
-
A.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
B.
officeHolderTitleInLatin
Indicates that the specified office holder’s title is expressed in its Latin-language form.
-
C.
officeHolderTitleInBulgarian
Indicates the official title or designation of an office holder as expressed in the Bulgarian language.
-
D.
officeHolderTitleInJapanese
Indicates the official title or designation of an office holder as expressed in the Japanese language.
-
E.
officeHolderTitleInGerman
Indicates the official title or designation of an office holder expressed in the German language.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c98e39081908904d36a31bd6768 |
completed | March 31, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:17 p.m.