Triple
T2228380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 19 |
E48706
|
entity |
| Predicate | hasAlternateRoute |
P19868
|
FINISHED |
| Object | U.S. Route 19E |
—
|
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 19E | Statement: [U.S. Route 19, hasAlternateRoute, U.S. Route 19E]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateRoute Context triple: [U.S. Route 19, hasAlternateRoute, U.S. Route 19E]
-
A.
alternativeRoute
chosen
Indicates that there exists a different path or option that can be taken instead of the primary or original route.
-
B.
hasAlternativeZoneInCountry
Indicates that an entity has an alternative zone or area located within the specified country.
-
C.
hasTransportRoute
Indicates that there exists a designated transportation connection or route linking one entity to another.
-
D.
hasEasiestRoute
Indicates that one entity provides or represents the simplest or least difficult route or path to reach another entity or destination.
-
E.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0670ce48190b98814064bff0517 |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.