Triple
T10074107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bertram, Iowa |
E213704
|
entity |
| Predicate | populationDensityPerSqMi2010 |
P728
|
FINISHED |
| Object | about 120.7 |
—
|
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: about 120.7 | Statement: [Bertram, Iowa, populationDensityPerSqMi2010, about 120.7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationDensityPerSqMi2010 Context triple: [Bertram, Iowa, populationDensityPerSqMi2010, about 120.7]
-
A.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
-
B.
rankInUS2010Census
Indicates the numerical position of an entity in the ranking of occurrences within the 2010 United States Census.
-
C.
hasPopulationDensity
chosen
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
D.
populationDensityRankInUS
Indicates the relative position of a place in a ranking of U.S. locations ordered by population density.
-
E.
hasPopulationDensityType
Indicates the classification of an area based on how densely populated it is (e.g., urban, suburban, rural).
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd015ad488190aee3a2bfb58fb855 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.