Triple
T9917731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberec Region |
E185911
|
entity |
| Predicate | NUTS_code |
P2415
|
FINISHED |
| Object | CZ051 |
—
|
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: CZ051 | Statement: [Liberec Region, NUTS_code, CZ051]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NUTS_code Context triple: [Liberec Region, NUTS_code, CZ051]
-
A.
NUTSRegionCode
chosen
Indicates the classification of an entity according to the NUTS (Nomenclature of Territorial Units for Statistics) regional coding system used for statistical regions.
-
B.
inseeCode
Indicates the official INSEE (French national statistics institute) code assigned to an entity, typically identifying a specific geographic or administrative unit.
-
C.
cantonCode
Indicates the specific administrative canton identifier associated with an entity or location.
-
D.
topLevelAdministrativeTerritorialEntity
Indicates that one entity is the primary or highest-level administrative territorial division in which the other entity is located or governed.
-
E.
federalStateCode
Indicates that an entity is associated with, governed by, or identified through a specific federal state code within a country’s administrative or legal system.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb5673f108190914e0c172dddc65f |
completed | April 2, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69cd1d90b8a8819081748f129c0c6ab6 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:42 p.m.