Triple
T28062951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciskei |
E709163
|
entity |
| Predicate | usedPassLawsToControlMovement |
P19759
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ciskei, usedPassLawsToControlMovement, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedPassLawsToControlMovement Context triple: [Ciskei, usedPassLawsToControlMovement, yes]
-
A.
usesLawTo
Indicates that one entity applies or relies on a specific law as a means or tool to affect, regulate, or influence another entity or situation.
-
B.
enforcesLawThrough
Indicates that one entity upholds, applies, or executes laws or legal rules by means of another entity, mechanism, or process.
-
C.
usedToRestrictEmigrationFrom
chosen
Indicates that something was employed as a means to limit or control people leaving a particular place or country.
-
D.
enforcedLaw
Indicates that an authority actively applies or upholds a specific law to regulate behavior or resolve situations.
-
E.
usedToRestrictEmigrationTo
Indicates that an entity implemented measures or policies to limit or control people leaving a particular place or jurisdiction.
- 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_69ef9b6eb6d88190a3fea236eb0f7bed |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641def1e88190a05bf865ced78b23 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 8:41 p.m.