Triple
T24389612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 13 corridor |
E614849
|
entity |
| Predicate | containsHighwaySegment |
P110379
|
FINISHED |
| Object | U.S. Route 13 in Delaware |
—
|
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 13 in Delaware | Statement: [U.S. Route 13 corridor, containsHighwaySegment, U.S. Route 13 in Delaware]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsHighwaySegment Context triple: [U.S. Route 13 corridor, containsHighwaySegment, U.S. Route 13 in Delaware]
-
A.
highwaySegment
chosen
Indicates a road section that forms part of a larger highway route.
-
B.
hasFreewaySegments
Indicates that one entity includes, contains, or is associated with specific freeway segments as part of its structure or network.
-
C.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
D.
hasGreenwaySegment
Indicates that an entity includes, is connected to, or is composed of one or more segments of a greenway path or corridor.
-
E.
isLocatedOnHighway
Indicates that one entity is situated along, adjacent to, or directly accessible from a specific highway.
- 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29457a0d08190ad19b55625d7a437 |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:04 a.m.