Triple
T25800026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester, Maryland |
E649796
|
entity |
| Predicate | hasMajorBridgeAccess |
P36619
|
FINISHED |
| Object | Chesapeake Bay Bridge |
—
|
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: Chesapeake Bay Bridge | Statement: [Chester, Maryland, hasMajorBridgeAccess, Chesapeake Bay Bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorBridgeAccess Context triple: [Chester, Maryland, hasMajorBridgeAccess, Chesapeake Bay Bridge]
-
A.
hasMajorBridge
Indicates that one entity possesses or includes a primary or significant bridge associated with it.
-
B.
hasBridgeAccess
Indicates that an entity is permitted to enter or use a specific bridge or bridge-controlled area.
-
C.
hasBridgeTo
chosen
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
D.
hasNumberOfBridges
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
-
E.
hasBridgeCrossings
Indicates that one entity has one or more bridge structures that span across or connect over another entity (such as a road, river, or area).
- 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_69e7ab34f8c8819099f6c4dabdabf129 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 22, 2026, 6:36 a.m.