Triple
T12228412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 香港特別行政區行政長官 |
E291412
|
entity |
| Predicate | 連任限制 |
P103901
|
FINISHED |
| Object | 最多連任一次 |
—
|
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: 最多連任一次 | Statement: [香港特別行政區行政長官, 連任限制, 最多連任一次]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 連任限制 Context triple: [香港特別行政區行政長官, 連任限制, 最多連任一次]
-
A.
mayoralReelectionLimit
Indicates the maximum number of times a person can be reelected to the office of mayor.
-
B.
limitedReelectionOfGovernor
Indicates that the governor’s ability to be reelected is restricted, such as by term limits or a cap on consecutive terms.
-
C.
eligibleForReelectionAfter
Indicates that an individual is permitted, under the relevant rules or laws, to run again for a position or office after a specified time or condition is met.
-
D.
termLimitDefinedBy
Indicates that the duration or number of terms for holding a position is specified or constrained by a particular rule, law, or authority.
-
E.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d92468052c819090546f36d009a64f |
completed | April 10, 2026, 4:25 p.m. |
Created at: April 8, 2026, 9:51 p.m.