Triple
T13903247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor of Hangzhou |
E334280
|
entity |
| Predicate | rankInChineseAdministrativeHierarchy |
P111950
|
FINISHED |
| Object | vice-provincial level |
—
|
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: vice-provincial level | Statement: [Mayor of Hangzhou, rankInChineseAdministrativeHierarchy, vice-provincial level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInChineseAdministrativeHierarchy Context triple: [Mayor of Hangzhou, rankInChineseAdministrativeHierarchy, vice-provincial level]
-
A.
rankInChinaByArea
Indicates the position of an entity in an ordered list of entities in China when sorted by their area size.
-
B.
administrativeHierarchyLevelInVietnam
Indicates the specific tier or rank an administrative unit occupies within Vietnam’s official governmental hierarchy.
-
C.
ChinaPosition
Indicates the stance, policy, or viewpoint officially held or expressed by China regarding a particular issue, event, or entity.
-
D.
hasAreaRankInTaiwan
Indicates the relative ranking of an entity by its area size compared to other entities within Taiwan.
-
E.
rankingByLengthInChina
Indicates that entities are ordered or evaluated based on their length within the context of China.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:16 p.m.