Triple
T262180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | China |
E5561
|
entity |
| Predicate | drivingForceOfEconomy |
P7347
|
FINISHED |
| Object | manufacturing |
—
|
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: manufacturing | Statement: [China, drivingForceOfEconomy, manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drivingForceOfEconomy Context triple: [China, drivingForceOfEconomy, manufacturing]
-
A.
economicSystem
Indicates the type or structure of the economic organization or system under which an entity operates or to which it belongs.
-
B.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
C.
economyIncludes
chosen
Indicates that an economy encompasses, contains, or is composed of the specified component, sector, or element.
-
D.
economicTrend
Indicates the general direction or pattern of economic activity or conditions over a period of time.
-
E.
economicRationale
Indicates the underlying economic reasoning or justification that explains why a particular decision, action, or relationship is expected to be financially or resource-efficient.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b6c968c819094fc903a3a377e15 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.