Triple
T6421706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongfeng Liuzhou Motor |
E127957
|
entity |
| Predicate | hasManufacturingActivity |
P26032
|
FINISHED |
| Object | vehicle assembly |
—
|
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: vehicle assembly | Statement: [Dongfeng Liuzhou Motor, hasManufacturingActivity, vehicle assembly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManufacturingActivity Context triple: [Dongfeng Liuzhou Motor, hasManufacturingActivity, vehicle assembly]
-
A.
hasProduction
chosen
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
B.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
-
C.
hasEconomicActivity
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
hasMajorProductionSystem
Indicates that an entity primarily operates, utilizes, or is characterized by a particular major production system.
- 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_69c0083815208190a9b299b8e0640218 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06903f67c8190a1e5babeede4e183 |
completed | March 22, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69c060f5d4e481909d1366190607b586 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:43 p.m.