Triple
T2698962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Lee Ka-chiu |
E58583
|
entity |
| Predicate | reasonForSanctions |
P42046
|
FINISHED |
| Object | role in implementing Hong Kong national security law |
—
|
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: role in implementing Hong Kong national security law | Statement: [John Lee Ka-chiu, reasonForSanctions, role in implementing Hong Kong national security law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForSanctions Context triple: [John Lee Ka-chiu, reasonForSanctions, role in implementing Hong Kong national security law]
-
A.
typeOfSanction
Indicates the specific category or kind of sanction that is applied in a given situation.
-
B.
canImposeSanctions
Indicates that one entity has the authority or power to apply punitive or restrictive measures (sanctions) against another entity.
-
C.
sanction
Indicates the imposition of an official penalty or restrictive measure by an authority in response to certain actions or behaviors.
-
D.
conditionsLiftingOfSanctionsOn
Indicates that one entity specifies or determines the requirements under which sanctions imposed on another entity will be removed or relaxed.
-
E.
reasonForBan
Indicates the justification or cause that led to an entity being banned.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda339cf48190b9ae6b99137f005e |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd9ceec708190aa162399023b2273 |
completed | March 7, 2026, 7:54 a.m. |
Created at: March 6, 2026, 9:55 p.m.