Triple
T3093314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rapid City, South Dakota |
E64533
|
entity |
| Predicate | populationRankInSouthDakota |
P21163
|
FINISHED |
| Object | second-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: second-largest city | Statement: [Rapid City, South Dakota, populationRankInSouthDakota, second-largest city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInSouthDakota Context triple: [Rapid City, South Dakota, populationRankInSouthDakota, second-largest city]
-
A.
hasCountyNumberInSouthDakota
Indicates that an entity is associated with a specific officially assigned county number within the state of South Dakota.
-
B.
stateRank
chosen
Indicates the relative position or standing of an entity within a specific state-level ordering or hierarchy.
-
C.
rankByPopulationInColorado
Indicates the relative ordering of entities based on their population size within the state of Colorado.
-
D.
populationRankInCounty
Indicates the relative position of an entity in terms of population size compared to other entities within the same county.
-
E.
populationDensityRankInUS
Indicates the relative position of a place in a ranking of U.S. locations ordered by population density.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23876a4819095bfc28640d8c200 |
completed | March 8, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.