Triple
T23523890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan and Israel |
E574580
|
entity |
| Predicate | borderDemarcationIncludes |
P115250
|
FINISHED |
| Object | Wadi Araba boundary |
—
|
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: Wadi Araba boundary | Statement: [Jordan and Israel, borderDemarcationIncludes, Wadi Araba boundary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderDemarcationIncludes Context triple: [Jordan and Israel, borderDemarcationIncludes, Wadi Araba boundary]
-
A.
borderRegionsInclude
Indicates that the specified border area encompasses or contains the referenced regions within its boundaries.
-
B.
borderWithin
Indicates that one region’s border lies entirely inside the boundary of another region.
-
C.
borderDefinedBetween
Indicates that a boundary line or border is formally established between two geographic or political entities.
-
D.
borderSectionOf
chosen
Indicates that one entity represents a specific segment or portion of the overall border of another entity.
-
E.
borderRegion
Indicates a region that lies along or near the boundary separating two distinct geographic or political areas.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1ac71ec8881909bfb706efdc2518f |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:09 p.m.