Triple
T31317158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USBMR1400128 |
E798626
|
entity |
| Predicate | componentCountryCode |
P188434
|
FINISHED |
| Object | US |
—
|
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: US | Statement: [USBMR1400128, componentCountryCode, US]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: componentCountryCode Context triple: [USBMR1400128, componentCountryCode, US]
-
A.
associatedCountryCode
Indicates that there is a relationship linking something to the country identified by the given country code.
-
B.
providerCountry
Indicates the country that serves as the source or origin of the provider in the relationship.
-
C.
continentCode
Indicates the standardized code assigned to the continent with which an entity is associated.
-
D.
countryCodePart
Indicates that one entity is a segment or component of a standardized country code associated with another entity.
-
E.
parentCountryCode
Indicates that the value is the standardized country code of the country that has jurisdiction or primary association over the referenced entity.
- 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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba789c1188190973a919bfe2871f3 |
completed | May 6, 2026, 8:41 p.m. |
Created at: April 29, 2026, 9:15 p.m.