Triple
T16363278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kigali Genocide Memorial |
E397369
|
entity |
| Predicate | numberOfVictimsBuried |
P95901
|
FINISHED |
| Object | over 250000 |
—
|
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: over 250000 | Statement: [Kigali Genocide Memorial, numberOfVictimsBuried, over 250000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVictimsBuried Context triple: [Kigali Genocide Memorial, numberOfVictimsBuried, over 250000]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
numberOfInterred
chosen
Indicates the total count of individuals who are buried or interred at a given site or within a specified context.
-
C.
massGravesDiscovered
Indicates that previously unknown burial sites containing multiple bodies have been found.
-
D.
numberOfMassGraves
Indicates the quantity of mass graves associated with or present at a given entity or location.
-
E.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff3aada88190a6e01f04c494a6ac |
completed | April 18, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.