Triple
T33673685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skogrand |
E862695
|
entity |
| Predicate | hasPrimarySubdivisionName |
P141681
|
FINISHED |
| Object | Nes |
E537555
|
NE 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: Nes | Statement: [Skogrand, hasPrimarySubdivisionName, Nes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimarySubdivisionName Context triple: [Skogrand, hasPrimarySubdivisionName, Nes]
-
A.
hasPrimaryCountrySubdivision
Indicates that an entity is associated with a main or principal first-level administrative division (such as a state, province, or region) within a specific country.
-
B.
primarySubdivisionOf
Indicates that one administrative or territorial unit is the main first-level subdivision within a larger political or geographic entity.
-
C.
hasSubdivisionName3
Indicates that an entity has a third-level subdivision whose name is given by the associated value.
-
D.
hasSubdivisionNameLevel1
chosen
Indicates that an entity has a first-level subdivision (e.g., state, province, region) identified by a specific name.
-
E.
hasSubdivisionLabel
Indicates that an entity assigns a specific label or name to one of its subdivisions or component parts.
- F. None of above.
Provenance (4 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_69f34985885c8190914322f492e04703 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01bcd39760819081807a02eb1939d1 |
completed | May 11, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3665696a948190bbe1183034218e68 |
completed | June 20, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_6a01bc3f1c74819087580e3134affc60 |
completed | May 11, 2026, 11:23 a.m. |
Created at: May 1, 2026, 1:43 a.m.