Triple
T5792980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 29 and State Route 8 near Athens, Georgia |
E128439
|
entity |
| Predicate | hasComponentHighway |
P385
|
FINISHED |
| Object | U.S. Route 29 |
—
|
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 29 | Statement: [U.S. Route 29 and State Route 8 near Athens, Georgia, hasComponentHighway, U.S. Route 29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComponentHighway Context triple: [U.S. Route 29 and State Route 8 near Athens, Georgia, hasComponentHighway, U.S. Route 29]
-
A.
hasMajorHighway
chosen
Indicates that a location or area is served by or directly connected to a major highway route.
-
B.
connectsToHighway
Indicates that one location, road, or route has a direct access point or linkage to a highway.
-
C.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
D.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
E.
hasCarriagewayType
Indicates the specific structural or functional type of carriageway associated with a road segment (e.g., single, dual, or other carriageway configurations).
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a5870b88190bbfaac2782635128 |
completed | March 22, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.