Triple
T1592901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Emblem of the People's Republic of China |
E34214
|
entity |
| Predicate | cogwheelRepresents |
P29653
|
FINISHED |
| Object | industrial workers |
—
|
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: industrial workers | Statement: [National Emblem of the People's Republic of China, cogwheelRepresents, industrial workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cogwheelRepresents Context triple: [National Emblem of the People's Republic of China, cogwheelRepresents, industrial workers]
-
A.
numberOfSpokes
Indicates the count of individual spokes associated with or contained in a given object or structure.
-
B.
rollingStockGauge
Indicates that one rolling stock entity is designed to operate on tracks built to a specific track gauge standard.
-
C.
wheelType
Indicates the specific kind or category of wheel associated with an entity.
-
D.
reducedRepresentationOf
Indicates that one entity is a simplified, compressed, or lower-detail version of another entity while preserving its essential information or structure.
-
E.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
- F. None of above. chosen
Provenance (4 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a916d2fae48190aaac6b2a5e31a7cf |
completed | March 5, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:27 p.m.