Triple
T11254230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bročice camp |
E266395
|
entity |
| Predicate | typeOfCrimeScene |
P84849
|
FINISHED |
| Object | site of war crimes |
—
|
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: site of war crimes | Statement: [Bročice camp, typeOfCrimeScene, site of war crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCrimeScene Context triple: [Bročice camp, typeOfCrimeScene, site of war crimes]
-
A.
settingOfCrime
chosen
Indicates the location or environment in which a crime takes place.
-
B.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
C.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
D.
targetOfCrime
Indicates that the subject is the person, organization, or entity against whom the referenced crime is committed.
-
E.
detectiveType
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9346f4c8190b29c2cf3a29cd1d1 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.