Triple
T16904753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tikhvinsky District |
E424530
|
entity |
| Predicate | hasTypeOfMunicipality |
P10835
|
FINISHED |
| Object | municipal district |
—
|
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: municipal district | Statement: [Tikhvinsky District, hasTypeOfMunicipality, municipal district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfMunicipality Context triple: [Tikhvinsky District, hasTypeOfMunicipality, municipal district]
-
A.
hasMunicipalityType
chosen
Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
-
B.
isPartOfMunicipalityType
Indicates that one administrative unit or area belongs to, or is classified under, a specific type or category of municipality.
-
C.
hasMunicipalAgencyType
Indicates that a municipal agency is classified as having a specific organizational or functional type.
-
D.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
-
E.
hasMunicipalDistrict
Indicates that an administrative entity includes or is divided into one or more municipal districts as its subordinate units.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8df454c8190898ebdd75985e51c |
completed | April 18, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.