Triple
T219080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Saint Petersburg |
E4173
|
entity |
| Predicate | hasOfficeholderTitle |
P3342
|
FINISHED |
| Object | Governor of Saint Petersburg |
—
|
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: Governor of Saint Petersburg | Statement: [Government of Saint Petersburg, hasOfficeholderTitle, Governor of Saint Petersburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeholderTitle Context triple: [Government of Saint Petersburg, hasOfficeholderTitle, Governor of Saint Petersburg]
-
A.
officeHolderTitle
chosen
Indicates the official position or title held by a person in an office or role.
-
B.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
C.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
-
D.
appliesToOfficeholder
Indicates that something (such as a rule, benefit, restriction, or obligation) is applicable specifically to a person holding a particular office or official position.
-
E.
notableOfficeHolder
Indicates that an entity is a significant or distinguished holder of a particular office or position associated with another entity.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c5199d8819096736c11077adec3 |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5357bc8190b29a48e3053fb76d |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.