Triple
T4984351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomington, Minnesota |
E111963
|
entity |
| Predicate | populationRankInMinnesota |
P27978
|
FINISHED |
| Object | fifth-largest city |
—
|
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: fifth-largest city | Statement: [Bloomington, Minnesota, populationRankInMinnesota, fifth-largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInMinnesota Context triple: [Bloomington, Minnesota, populationRankInMinnesota, fifth-largest city]
-
A.
rankInMinnesotaByPopulation
chosen
Indicates the numerical position of an entity in an ordered list of Minnesota locations sorted by their population size.
-
B.
populationRankInMissouri
Indicates the relative position of an entity in terms of population size compared to other entities within the state of Missouri.
-
C.
populationRankInMaine
Indicates the relative position of an entity in terms of population size compared to other entities within the state of Maine.
-
D.
populationRankInMaryland
Indicates the relative position of an entity in terms of its population size compared to other entities within the state of Maryland.
-
E.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.