Triple
T15191013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Mbonga |
E363008
|
entity |
| Predicate | causeOfGrief |
P56982
|
FINISHED |
| Object | death of his son |
—
|
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: death of his son | Statement: [Chief Mbonga, causeOfGrief, death of his son]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfGrief Context triple: [Chief Mbonga, causeOfGrief, death of his son]
-
A.
mourningCause
chosen
Indicates that one entity is in a state of mourning specifically because of the other entity, which is the cause or reason for the grief.
-
B.
grievesFor
Indicates that one entity feels grief or sorrow because of the loss, suffering, or misfortune of another entity.
-
C.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
D.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
E.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067d55ac8190b7a7fce36e6ddf3c |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:10 a.m.