Triple
T8219640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nan’an District |
E192024
|
entity |
| Predicate | hasMajorAreaType |
P6822
|
FINISHED |
| Object | residential |
—
|
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: residential | Statement: [Nan’an District, hasMajorAreaType, residential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorAreaType Context triple: [Nan’an District, hasMajorAreaType, residential]
-
A.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
B.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
hasMajorType
Indicates that an entity belongs to or is categorized under a primary or overarching type or classification.
-
D.
hasMajorComponent
Indicates that one entity includes another entity as a primary or most significant component or part.
-
E.
hasMacroArea
Indicates that one entity belongs to, or is located within, a broader geographic or conceptual macro-area represented by another entity.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb7772b76c8190b1952650c736eb91 |
completed | March 31, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69cb36af41e081909dee92b9bc4947f1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:45 p.m.