Triple
T28373847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 竹山县 |
E718702
|
entity |
| Predicate | 特色产业 |
P154638
|
FINISHED |
| Object | 茶叶 |
—
|
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 | Statement: [竹山县, 特色产业, 茶叶]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 特色产业 Context triple: [竹山县, 特色产业, 茶叶]
-
A.
传统产业
Indicates an association with traditional industries, typically involving established, long-standing modes of production, technology, and business models.
-
B.
工业区位优势
Indicates the advantageous locational conditions that make a place particularly suitable or competitive for industrial development and operations.
-
C.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
D.
partOfLocalEconomy
chosen
Indicates that an entity contributes to, participates in, or is integrated within the economic activities of a specific local area or community.
-
E.
countryTourismCategory
Indicates the tourism classification or category assigned to a country based on its tourism characteristics or status.
- 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.