Triple
T15001147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuka trial of 1929 |
E374091
|
entity |
| Predicate | hasDefendantOccupation |
P99264
|
FINISHED |
| Object | Slovak nationalist leader |
—
|
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: Slovak nationalist leader | Statement: [Tuka trial of 1929, hasDefendantOccupation, Slovak nationalist leader]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDefendantOccupation Context triple: [Tuka trial of 1929, hasDefendantOccupation, Slovak nationalist leader]
-
A.
hasDefendantWork
Indicates that a particular work (such as a product, creation, or item) is associated with or attributed to the defendant in a legal context.
-
B.
defendantProfession
chosen
Indicates the professional occupation or job role held by the defendant in a legal case.
-
C.
defendantOccupationAtTime
Indicates that a defendant held a particular occupation or job role during a specified time period.
-
D.
hasPerpetratorOccupation
Indicates that the occupation or job role of the perpetrator involved in an act or incident is being specified.
-
E.
hasOccupationOfDesignee
Indicates that one entity serves as the designated or appointed holder of an occupation or role for 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded72fec948190b1c9705538c57976 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:54 a.m.