Triple
T17989256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lethbridge Bulls |
E430323
|
entity |
| Predicate | hasHomeCityPopulationRange |
P28398
|
FINISHED |
| Object | mid-sized 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: mid-sized city | Statement: [Lethbridge Bulls, hasHomeCityPopulationRange, mid-sized city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHomeCityPopulationRange Context triple: [Lethbridge Bulls, hasHomeCityPopulationRange, mid-sized city]
-
A.
populationRange
chosen
Indicates the numerical interval within which the size of a population falls.
-
B.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
C.
homeCityPopulationRegion
Indicates that the population of a home city falls within or is associated with a specified geographic region.
-
D.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
staffPopulationApprox
Indicates an approximate or estimated number of staff associated with an entity.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29e47a88190be58b79c73d3e652 |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.