Triple
T29286556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khajuwala tehsil |
E742528
|
entity |
| Predicate | hasInternationalBorderNearby |
P46305
|
FINISHED |
| Object | Pakistan |
—
|
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: Pakistan | Statement: [Khajuwala tehsil, hasInternationalBorderNearby, Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInternationalBorderNearby Context triple: [Khajuwala tehsil, hasInternationalBorderNearby, Pakistan]
-
A.
nearInternationalBoundary
chosen
Indicates that one entity is located close to an international boundary separating two or more countries.
-
B.
hasBorderWithinCountry
Indicates that one region or area shares an internal boundary with another region or area within the same country.
-
C.
connectsToCountryBorder
Indicates that one entity is directly adjacent to and touches the border of a specified country.
-
D.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
E.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
- 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_69f09121ed8c8190b4cb27be3619c262 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: April 28, 2026, 12:58 p.m.