Triple
T28883015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pike Township, Bradford County, Pennsylvania |
E732470
|
entity |
| Predicate | isLowDensity |
P148385
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Pike Township, Bradford County, Pennsylvania, isLowDensity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLowDensity Context triple: [Pike Township, Bradford County, Pennsylvania, isLowDensity, true]
-
A.
hasLowDensity
chosen
Indicates that the subject possesses a density value that is below a defined or typical threshold.
-
B.
lowDensityAreaUsedFor
Indicates that a low-density area is utilized for a particular purpose or function.
-
C.
hasLow
Indicates that an entity possesses a value, level, or amount of something that is below a defined or expected threshold.
-
D.
hasLowerColumnDensityLimitThan
Indicates that the column density of one entity is constrained to be lower than the column density of another entity.
-
E.
hasHighDensityOf
Indicates that one entity contains or exhibits a large concentration or amount of another entity within a given area, volume, or context.
- 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_69f05b07bdec819080cadfe147aa1f25 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65a6fc5088190af152ba43c0b91e5 |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 7:47 a.m.