Triple
T15055650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drachten |
E379482
|
entity |
| Predicate | hasPopulationRankInFriesland |
P25930
|
FINISHED |
| Object | one of the largest towns |
—
|
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: one of the largest towns | Statement: [Drachten, hasPopulationRankInFriesland, one of the largest towns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInFriesland Context triple: [Drachten, hasPopulationRankInFriesland, one of the largest towns]
-
A.
hasPopulationRankInRegion
chosen
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
-
B.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
hasPopulationRankInEstonia
Indicates the relative position of an entity in the ordered list of populations within Estonia, such as its rank by population size compared to other entities in the country.
-
D.
areaInundatedNetherlands
Indicates the extent of land in the Netherlands that is covered or flooded by water.
-
E.
chartPositionBelgiumFlanders
Indicates the position or ranking something holds on the music charts specifically in the Flanders region of Belgium.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda937f788190899d81bbb2084443 |
completed | April 15, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:01 a.m.