Triple
T24468424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RD-93 |
E617035
|
entity |
| Predicate | notableUserCountry |
P88655
|
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: [RD-93, notableUserCountry, Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableUserCountry Context triple: [RD-93, notableUserCountry, Pakistan]
-
A.
associatedCountryViaNotableBearer
Indicates a relationship where an entity is linked to a country through a notable person who bears or represents that entity (such as a name, title, or work).
-
B.
notableCountry
Indicates that a country holds particular significance or prominence in relation to the subject entity.
-
C.
userCountry
chosen
Indicates the country with which a given user is associated or located.
-
D.
associatedCountryMostProminently
Indicates the country with which an entity is most strongly or prominently associated, relative to any other countries it may be linked to.
-
E.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299413ea88190b15e482035ff5a83 |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.