Triple
T28373836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 竹山县 |
E718702
|
entity |
| Predicate | 农业产业 |
P93731
|
FINISHED |
| Object | 茶叶种植 |
—
|
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: 茶叶种植 | Statement: [竹山县, 农业产业, 茶叶种植]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 农业产业 Context triple: [竹山县, 农业产业, 茶叶种植]
-
A.
agriculturalFocus
chosen
Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
-
B.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
-
C.
传统产业
Indicates an association with traditional industries, typically involving established, long-standing modes of production, technology, and business models.
-
D.
agricultureBusinessTransferredTo
Indicates that control, ownership, or operation of an agricultural business is passed from one party to another.
-
E.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
- 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_69eff6ee5afc8190bd7375a29f0cc6c6 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64c5c0ba081908d836393db68b842 |
completed | May 2, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 1:01 a.m.