Triple
T18275977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giannitsa Plain |
E437733
|
entity |
| Predicate | administrativeProximity |
P61362
|
FINISHED |
| Object | near Thessaloniki regional unit |
—
|
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: near Thessaloniki regional unit | Statement: [Giannitsa Plain, administrativeProximity, near Thessaloniki regional unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeProximity Context triple: [Giannitsa Plain, administrativeProximity, near Thessaloniki regional unit]
-
A.
featuresRegionalProximity
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
B.
nearProvince
Indicates that one province is geographically close to or bordering another province.
-
C.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
D.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
-
E.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50051bccc8190832eacdb6945d6b7 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.