Triple
T13480891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gigiri, Nairobi |
E318367
|
entity |
| Predicate | hasDiplomaticMissionCluster |
P98893
|
FINISHED |
| Object | embassies |
—
|
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: embassies | Statement: [Gigiri, Nairobi, hasDiplomaticMissionCluster, embassies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiplomaticMissionCluster Context triple: [Gigiri, Nairobi, hasDiplomaticMissionCluster, embassies]
-
A.
hasDiplomaticMission
Indicates that one entity maintains an official diplomatic representation, such as an embassy or mission, in the territory or jurisdiction of another entity.
-
B.
diplomaticMissionInCity
chosen
Indicates that a diplomatic mission (such as an embassy or consulate) is located in or operates within a specific city.
-
C.
hasConsulateOfUnitedStatesIn
Indicates that a consulate of the United States is located in the specified place.
-
D.
haveConsulates
Indicates that one country maintains consular offices or consulates within the territory of another country.
-
E.
hasConsularSection
Indicates that an entity (typically a diplomatic mission or embassy) includes or is associated with a consular section responsible for consular services.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf36c6b08190ba99400600e0b662 |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbae06061881909a6a6032e0507587 |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.