Triple
T584695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gainesville, Virginia |
E15132
|
entity |
| Predicate | growthDriver |
P7907
|
FINISHED |
| Object | proximity to Washington, D.C. |
—
|
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: proximity to Washington, D.C. | Statement: [Gainesville, Virginia, growthDriver, proximity to Washington, D.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: growthDriver Context triple: [Gainesville, Virginia, growthDriver, proximity to Washington, D.C.]
-
A.
growthForm
Indicates the physical structure or habit in which something develops or grows (such as its overall shape, form, or growth pattern).
-
B.
accelerates
Indicates that one entity causes an increase in the speed or rate of change of another entity or process.
-
C.
increases
chosen
Indicates that one entity causes another entity’s value, level, or intensity to become larger or higher.
-
D.
goals
Indicates that an entity has objectives, targets, or desired outcomes it aims to achieve.
-
E.
legacyGoal
Indicates that an entity has a long-term, enduring objective or impact it aims to leave behind beyond its immediate actions or existence.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9874c88190bd1e08d4689ea124 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.