Triple
T36012048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volvo CMA platform |
E1041737
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object |
Geely BMA platform
The Geely BMA platform is a modular vehicle architecture developed by Geely for its compact cars and crossovers, serving as a cost-effective counterpart to the more advanced Volvo CMA platform within the Geely group.
|
E2165232
|
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: Geely BMA platform | Statement: [Volvo CMA platform, relatedTo, Geely BMA platform]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Geely BMA platform Triple: [Volvo CMA platform, relatedTo, Geely BMA platform]
Generated description
The Geely BMA platform is a modular vehicle architecture developed by Geely for its compact cars and crossovers, serving as a cost-effective counterpart to the more advanced Volvo CMA platform within the Geely group.
Provenance (5 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_69f76e2b981881908e4e160607fa82eb |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acb462e88190b6429ca5e8c7bb73 |
completed | May 3, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38bffa789c8190ad0eacda673adc9f |
completed | June 22, 2026, 4:54 a.m. |
| NEDg | Description generation | batch_6a38c0b9e5508190ae451756483ea6f8 |
completed | June 22, 2026, 4:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a38c14a3b6c81908d6bcb4ed8316a28 |
completed | June 22, 2026, 4:59 a.m. |
Created at: May 3, 2026, 4:07 p.m.