Triple
T13574386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volvo S90 |
E324243
|
entity |
| Predicate | assemblyLocation |
P40
|
FINISHED |
| Object | Daqing, China |
E520233
|
NE 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: Daqing, China | Statement: [Volvo S90, assemblyLocation, Daqing, China]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daqing, China Context triple: [Volvo S90, assemblyLocation, Daqing, China]
-
A.
Daqing
chosen
Daqing is a major industrial city in northeastern China best known for its large oil fields and role as a center of the country’s petroleum industry.
-
B.
Baicheng
Baicheng is a prefecture-level city in northwestern Jilin Province in northeastern China, known for its agriculture and location near the borders with Inner Mongolia and Heilongjiang.
-
C.
Hegang
Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
-
D.
Mudanjiang
Mudanjiang is a prefecture-level city in southeastern Heilongjiang Province in northeastern China, known as a regional transport hub and gateway to nearby scenic and border areas.
-
E.
Shuangyashan
Shuangyashan is a coal-mining and industrial city in northeastern China known for its energy resources and heavy industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bba21f88190b8952fb0879e623d |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.