Triple
T34784926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 50 in Maryland |
E1002777
|
entity |
| Predicate | bridgeTypeSection |
P181610
|
FINISHED |
| Object | freeway for much of its length in Maryland |
—
|
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: freeway for much of its length in Maryland | Statement: [U.S. Route 50 in Maryland, bridgeTypeSection, freeway for much of its length in Maryland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bridgeTypeSection Context triple: [U.S. Route 50 in Maryland, bridgeTypeSection, freeway for much of its length in Maryland]
-
A.
bridgeType
Indicates the specific kind or classification of a bridge associated with an entity.
-
B.
bridgeStructure
Indicates a structural relationship where one entity functions as a bridge that spans or connects two separate points or areas.
-
C.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
D.
bridgeLocation
Indicates the specific place or area where a bridge is situated or spans.
-
E.
bridgeFeature
Indicates that one entity functions as a structural or functional feature of a bridge associated with another entity.
- 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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77ff804f08190b431a31e6179ace4 |
completed | May 3, 2026, 5:03 p.m. |
Created at: May 3, 2026, 3:59 p.m.