Triple
T29025266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korukivka |
E737573
|
entity |
| Predicate | massacreOccurredIn |
P165933
|
FINISHED |
| Object | 1943 |
—
|
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: 1943 | Statement: [Korukivka, massacreOccurredIn, 1943]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: massacreOccurredIn Context triple: [Korukivka, massacreOccurredIn, 1943]
-
A.
massacreOccurred
Indicates that a large-scale, deliberate killing of multiple individuals took place in a specific event or context.
-
B.
massacreAlsoKnownAs
Indicates that a particular massacre is known or referred to by an alternative name or names.
-
C.
notableMassKillingSite
Indicates that a place is recognized as a significant location where a mass killing or massacre occurred.
-
D.
massacreOrderedBy
Indicates that a massacre was carried out under the command, authorization, or directive of a particular person or authority.
-
E.
massacreCasualtiesEstimate
Indicates an estimated number of people who were killed or injured as a result of a massacre.
- F. None of above. chosen
Provenance (4 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66008ba1c8190b629678511f36c99 |
completed | May 2, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65ad638ac8190a17bb987fce53279 |
completed | May 2, 2026, 8:13 p.m. |
Created at: April 28, 2026, 9:52 a.m.