Triple
T3823086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beneš decrees |
E88620
|
entity |
| Predicate | legalStatusIn |
P15012
|
FINISHED |
| Object | still formally valid in Czech Republic |
—
|
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: still formally valid in Czech Republic | Statement: [Beneš decrees, legalStatusIn, still formally valid in Czech Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusIn Context triple: [Beneš decrees, legalStatusIn, still formally valid in Czech Republic]
-
A.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
B.
legalStatusClarifiedBy
chosen
Indicates that the legal status of something is defined, explained, or resolved by a specific document, decision, or authoritative act.
-
C.
legalStatusVariesBy
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
D.
legalStatusModern
Indicates the current legal standing or classification of an entity under contemporary law or regulatory frameworks.
-
E.
legalStatusInManyCountries
Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.