Triple
T16925266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minita_Gordon |
E410556
|
entity |
| Predicate | inceptionAsGovernorGeneral |
P95676
|
FINISHED |
| Object | after independence of Belize |
—
|
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: after independence of Belize | Statement: [Minita_Gordon, inceptionAsGovernorGeneral, after independence of Belize]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inceptionAsGovernorGeneral Context triple: [Minita_Gordon, inceptionAsGovernorGeneral, after independence of Belize]
-
A.
startTimeAsGovernorGeneral
chosen
Indicates the point in time when an individual began serving in the role of Governor General.
-
B.
termStartAsGovernorGeneralOfIndia
Indicates the date or point in time when an individual began their tenure as Governor-General of India.
-
C.
designatedAsFirstGovernorGeneralOfIndia
Indicates that one entity was formally designated or recognized as the first Governor-General of India in relation to the other entity.
-
D.
openedAsGovernorGeneralOffice
Indicates that an entity was inaugurated or began operation in the capacity of a Governor General’s office.
-
E.
madeGovernorGeneralOfBengal
Indicates that a person was appointed to the position of Governor-General of Bengal.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cdf1ebdc8190b39a9469636de01e |
completed | April 18, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69e32b982f548190b08414d55810de19 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:30 a.m.