Triple
T30557884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novocherkassk massacre |
E777750
|
entity |
| Predicate | coverUp |
P25172
|
FINISHED |
| Object | bodies buried in unmarked graves |
—
|
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: bodies buried in unmarked graves | Statement: [Novocherkassk massacre, coverUp, bodies buried in unmarked graves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverUp Context triple: [Novocherkassk massacre, coverUp, bodies buried in unmarked graves]
-
A.
coverUpBy
chosen
Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
-
B.
coverVersionBy
Indicates that one creative work is a cover version performed or produced by a particular artist or entity.
-
C.
cover
Indicates that one entity extends over, conceals, protects, or provides a surface or layer for another entity.
-
D.
coverText
Indicates that one text serves as the cover or front-facing textual representation for another work or resource.
-
E.
usedCover
Indicates that one entity employed another entity as a protective or concealing cover in a given context.
- 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_69f2249ed41c8190b175170ecfd6e1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 29, 2026, 8:21 p.m.