Triple
T3882230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norid |
E92850
|
entity |
| Predicate | countryCodeManaged |
P52127
|
FINISHED |
| Object | NO |
—
|
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: NO | Statement: [Norid, countryCodeManaged, NO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCodeManaged Context triple: [Norid, countryCodeManaged, NO]
-
A.
countryCodePart
Indicates that one entity is a segment or component of a standardized country code associated with another entity.
-
B.
associatedCountryCode
Indicates that there is a relationship linking something to the country identified by the given country code.
-
C.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
-
D.
FIPSCountryCode
Indicates that an entity is associated with a specific country as identified by its FIPS (Federal Information Processing Standards) country code.
-
E.
usedByCountryCode
Indicates that something is utilized or applied within the country identified by the given country code.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.