Triple
T24567081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Route 376 |
E607819
|
entity |
| Predicate | populationDensityAlongRoute |
P23004
|
FINISHED |
| Object | sparsely populated |
—
|
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: sparsely populated | Statement: [State Route 376, populationDensityAlongRoute, sparsely populated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationDensityAlongRoute Context triple: [State Route 376, populationDensityAlongRoute, sparsely populated]
-
A.
roadNetworkDensity
Indicates the concentration of roads within a given area, reflecting how densely the transportation network is developed.
-
B.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
-
C.
cityAlongRoute
Indicates that a given city lies on or is passed through by a specified route or path.
-
D.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
E.
populationConcentration
chosen
Indicates the degree to which a population is densely gathered or distributed within a specific area or region.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a92141f88190bcbd7c6aeafc0725 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:28 a.m.