Triple
T37824601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Bravo, Tamaulipas |
E943016
|
entity |
| Predicate | hasBorderStateAcrossRiver |
P143613
|
FINISHED |
| Object | Texas |
—
|
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: Texas | Statement: [Rio Bravo, Tamaulipas, hasBorderStateAcrossRiver, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderStateAcrossRiver Context triple: [Rio Bravo, Tamaulipas, hasBorderStateAcrossRiver, Texas]
-
A.
borderedByCountryAcrossRiver
Indicates that one country shares a border with another country, with the boundary specifically formed or separated by a river.
-
B.
crossesBorderRiver
Indicates that one entity moves from one side of a border-defining river to the other, traversing the river that serves as a boundary.
-
C.
bordersAcrossRiver
chosen
Indicates that two regions or entities share a boundary with each other that is separated or defined by a river.
-
D.
crossesBorderOf
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
E.
hasRiverCrossingType
Indicates the type or nature of a river crossing associated with an entity (e.g., bridge, ford, ferry).
- 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_69f76ee987588190906506e759be5db3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
Created at: May 3, 2026, 4:19 p.m.