Triple
T30460850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Route 737 |
E775000
|
entity |
| Predicate | connectsToMajorRoute |
P143989
|
FINISHED |
| Object | U.S. Route 222 |
—
|
NE NERFINISHED |
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: U.S. Route 222 | Statement: [Pennsylvania Route 737, connectsToMajorRoute, U.S. Route 222]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToMajorRoute Context triple: [Pennsylvania Route 737, connectsToMajorRoute, U.S. Route 222]
-
A.
isMajorRouteThrough
Indicates that a route serves as a primary or significant pathway passing through a specified area or location.
-
B.
onMajorRouteBetween
Indicates that one location lies along a primary or major route connecting two other locations.
-
C.
hasMajorRouteType
Indicates that an entity is associated with a primary classification of transportation route (such as highway, rail line, or other major route type).
-
D.
connectsToMajorLineServing
chosen
Indicates that one transportation line or route is directly linked to a primary or high-capacity line that provides major service coverage.
-
E.
isMajorRouteFor
Indicates that something serves as a primary or heavily used pathway or channel for the movement or flow of something else.
- 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_69f22494fb60819095d893de0284f886 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: April 29, 2026, 8:10 p.m.