Triple
T31231117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Route 16 |
E796283
|
entity |
| Predicate | crossesStateLineAt |
P13760
|
FINISHED |
| Object | Maryland–Pennsylvania state line |
—
|
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: Maryland–Pennsylvania state line | Statement: [Pennsylvania Route 16, crossesStateLineAt, Maryland–Pennsylvania state line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesStateLineAt Context triple: [Pennsylvania Route 16, crossesStateLineAt, Maryland–Pennsylvania state line]
-
A.
crossesStateBoundaryViaBridgeTo
Indicates that one entity crosses a state boundary to reach another entity specifically by traveling over a bridge.
-
B.
crossesInternationalBoundaryAt
Indicates that one entity passes from one country’s territory into another at a specific boundary location.
-
C.
crossesCityLimit
Indicates that an entity moves from outside to inside, or inside to outside, the defined boundary of a city.
-
D.
crossesBorderOf
chosen
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
E.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: April 29, 2026, 9:10 p.m.