Triple
T20768452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 31E |
E511162
|
entity |
| Predicate | hasSisterRoute |
P106087
|
FINISHED |
| Object | U.S. Route 31W |
—
|
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 31W | Statement: [U.S. Route 31E, hasSisterRoute, U.S. Route 31W]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSisterRoute Context triple: [U.S. Route 31E, hasSisterRoute, U.S. Route 31W]
-
A.
hasCompanionRoute
chosen
Indicates that one route is associated with another route that serves as its companion, typically running in parallel, in the opposite direction, or as a complementary service.
-
B.
hasSisterSubsystem
Indicates that one subsystem is related to another as a sister subsystem, meaning they share a common parent system or hierarchical level.
-
C.
hasSisterProperty
Indicates that one property is related to another as a sister property, typically sharing a common parent or similar hierarchical level.
-
D.
hasSisterRelationshipType
Indicates that there exists a sister-type familial relationship between the related entities.
-
E.
hasSisterChannel
Indicates that one media channel is related to another as its sister channel, typically under common ownership or branding.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24fa1b08190b09ab8fcb87b5c01 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0550ec481908a0877fb2409d983 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:36 p.m.