Triple
T21364119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Sugar Creek |
E526863
|
entity |
| Predicate | hasGreenwaySegment |
P143987
|
FINISHED |
| Object | Midtown Greenway segment |
—
|
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: Midtown Greenway segment | Statement: [Little Sugar Creek, hasGreenwaySegment, Midtown Greenway segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenwaySegment Context triple: [Little Sugar Creek, hasGreenwaySegment, Midtown Greenway segment]
-
A.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
B.
hasFreewaySegments
Indicates that one entity includes, contains, or is associated with specific freeway segments as part of its structure or network.
-
C.
hasRightOfWayNetwork
Indicates that one transportation route or entity is part of, or associated with, a designated right-of-way network used for movement or access.
-
D.
hasScenicRouteType
Indicates that a route is associated with a specific type or category of scenic quality or scenic designation.
-
E.
hasScenicRouteStatus
Indicates that a route or path possesses a designated scenic status, typically recognized for its visual appeal or noteworthy landscapes.
- F. None of above. chosen
Provenance (4 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b06d6dcc8190b438d3c2e620578c |
completed | April 22, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e61b3e47f881908fb2aac9bd2bfb58 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 16, 2026, 5:08 p.m.