Triple
T16632988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabethpol Governor |
E404121
|
entity |
| Predicate | officeHolderTitleInAzerbaijani |
P123656
|
FINISHED |
| Object | Yelizavetpol qubernatoru |
—
|
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: Yelizavetpol qubernatoru | Statement: [Elisabethpol Governor, officeHolderTitleInAzerbaijani, Yelizavetpol qubernatoru]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderTitleInAzerbaijani Context triple: [Elisabethpol Governor, officeHolderTitleInAzerbaijani, Yelizavetpol qubernatoru]
-
A.
officeHolderTitleInTurkish
Indicates the official title or designation of an office holder expressed in the Turkish language.
-
B.
officeHolderTitleInArabic
Indicates the official title or designation of an office holder expressed in the Arabic language.
-
C.
officeHolderTitleInRussian
Indicates the official title or designation of an office holder expressed in the Russian language.
-
D.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
E.
officeHolderTitleInHungarian
Indicates the official title or designation of an office holder expressed in the Hungarian 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e7d4a48190a9b4a14ecbb2a14b |
completed | April 18, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.