Triple
T21652290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petrolina–Juazeiro metropolitan area |
E534367
|
entity |
| Predicate | isBinationalUrbanArea |
P144875
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Petrolina–Juazeiro metropolitan area, isBinationalUrbanArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBinationalUrbanArea Context triple: [Petrolina–Juazeiro metropolitan area, isBinationalUrbanArea, true]
-
A.
isBinational
Indicates that an entity is associated with or recognized by two distinct nations, such as holding dual nationality or operating under the authority of two countries.
-
B.
isBinationalComponentOf
Indicates that an entity is a component or part of a larger structure, project, or system that is jointly established, managed, or recognized by two nations.
-
C.
hasMajorBinationalComponent
Indicates that something involves a significant component jointly undertaken, governed, or shared by two different nations.
-
D.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
-
E.
isBilingualRegion
Indicates that a region officially uses two languages or has two predominant languages in regular use.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:36 p.m.