Triple
T37102724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Contra Costa County and Solano County |
E918747
|
entity |
| Predicate | areOppositeSidesOf |
P36358
|
FINISHED |
| Object | Carquinez Strait |
—
|
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: Carquinez Strait | Statement: [Contra Costa County and Solano County, areOppositeSidesOf, Carquinez Strait]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areOppositeSidesOf Context triple: [Contra Costa County and Solano County, areOppositeSidesOf, Carquinez Strait]
-
A.
isOneOfSidesOf
Indicates that an entity is one of the boundary edges or lateral faces that form part of another entity.
-
B.
isBSideOf
Indicates that one entity is located on the B side or secondary face of another entity, typically in a two-sided or dual-orientation context.
-
C.
isOnSideAOrB
Indicates that an entity is located on either side A or side B of a specified reference or boundary.
-
D.
hasOpposingSide
chosen
Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
-
E.
hasOppositeDirectionTo
Indicates that one entity’s direction is exactly reversed or opposed to the direction of another entity.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb344c60f8819090f2e21e1e61d621 |
completed | May 6, 2026, 12:30 p.m. |
| PD | Predicate disambiguation | batch_69fb2f642db08190b562725502c74ea6 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.