Triple
T34615864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kommunalreformen 2007 |
E888861
|
entity |
| Predicate | previousNumberOfCounties |
P27148
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Kommunalreformen 2007, previousNumberOfCounties, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousNumberOfCounties Context triple: [Kommunalreformen 2007, previousNumberOfCounties, 13]
-
A.
previousCounty
Indicates that one county was the immediately preceding county associated with an entity before the current or later county.
-
B.
hasNumberOfCounties
chosen
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
C.
hasFormerCounty
Indicates that an entity was previously part of, or administered by, a particular county in the past but no longer is.
-
D.
numberPerCounty
Indicates the quantity or count of something associated with each individual county.
-
E.
countyNumberInStateFormation
Indicates the ordinal position a county held among all counties created within a particular state at the time of that state's formation.
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
Created at: May 1, 2026, 2:03 a.m.