Triple
T4962246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanshan District |
E111435
|
entity |
| Predicate | hasCityLevel |
P27799
|
FINISHED |
| Object | district-level division |
—
|
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: district-level division | Statement: [Nanshan District, hasCityLevel, district-level division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityLevel Context triple: [Nanshan District, hasCityLevel, district-level division]
-
A.
cityLevel
Indicates the administrative or hierarchical rank of a city within a broader regional or national structure.
-
B.
hasCountyLevelCity
chosen
Indicates that an entity (typically a region or province) includes or administers one or more cities that hold county-level administrative status.
-
C.
hasMetropolitan
Indicates that an entity is associated with, served by, or located within a specific metropolitan area.
-
D.
hasMajorCity
Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
-
E.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
- 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_69bd4419393c819086319a6fe4bf8542 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd72e49b048190bac55d9e7a6f7963 |
completed | March 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69bd71447fe88190bb62c5e8753da7a7 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:32 p.m.