Triple
T34818723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vari-Voula-Vouliagmeni |
E1003707
|
entity |
| Predicate | containsMunicipalUnit |
P84684
|
FINISHED |
| Object | Vari |
—
|
NE NERFINISHED |
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: Vari | Statement: [Vari-Voula-Vouliagmeni, containsMunicipalUnit, Vari]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMunicipalUnit Context triple: [Vari-Voula-Vouliagmeni, containsMunicipalUnit, Vari]
-
A.
hasMunicipalUnitName
Indicates that an entity is associated with the specific name of a municipal unit (such as a town, district, or local administrative division).
-
B.
hasMunicipalPart
chosen
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
C.
isInMunicipality
Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
-
D.
oftenIncludesMunicipality
Indicates that one entity frequently or typically contains or encompasses a municipality within its boundaries or scope.
-
E.
hasMunicipalUnitArea
Indicates that a municipal unit is associated with a specific measured area.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a008c77d4dc8190b342d7407eaf48fa |
completed | May 10, 2026, 1:47 p.m. |
| PD | Predicate disambiguation | batch_6a008c18531c8190bbe883b73e6d023f |
completed | May 10, 2026, 1:46 p.m. |
Created at: May 3, 2026, 4 p.m.