Triple
T34615912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish regions |
E888862
|
entity |
| Predicate | includeSubdivision |
P747
|
FINISHED |
| Object | Region Hovedstaden |
E129472
|
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: Region Hovedstaden | Statement: [Danish regions, includeSubdivision, Region Hovedstaden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includeSubdivision Context triple: [Danish regions, includeSubdivision, Region Hovedstaden]
-
A.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
B.
isSubdivisionUsedFor
Indicates that a particular subdivision (such as a region, section, or part of something) is utilized for a specified purpose or function.
-
C.
subdivisionFlagOf
Indicates that one administrative or territorial unit is a designated subdivision or sub-part of another unit.
-
D.
hasSubdivisionStandard
Indicates that a governing standard or specification defines how an entity is to be subdivided into smaller parts or units.
-
E.
hasSubdivisionCode
Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3748e6f150819086197fae9aa72251 |
completed | June 21, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:03 a.m.