Triple
T37706963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia World 2010 |
E939221
|
entity |
| Predicate | featuredDevice |
P35865
|
FINISHED |
| Object |
Nokia C7
The Nokia C7 is a mid-range Symbian^3 smartphone released in 2010, known for its sleek design, AMOLED touchscreen, and focus on social networking and multimedia features.
|
E2239217
|
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: Nokia C7 | Statement: [Nokia World 2010, featuredDevice, Nokia C7]
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: Nokia C7 Triple: [Nokia World 2010, featuredDevice, Nokia C7]
Generated description
The Nokia C7 is a mid-range Symbian^3 smartphone released in 2010, known for its sleek design, AMOLED touchscreen, and focus on social networking and multimedia features.
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_69f76edb49dc8190b951dce9ce6ef789 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a03809e663c819080cff52d0377d81f |
completed | May 12, 2026, 7:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40cdcc510c81908706236083878622 |
completed | June 28, 2026, 7:31 a.m. |
| NEDg | Description generation | batch_6a40ce7402cc8190abf4f70571b98544 |
completed | June 28, 2026, 7:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a40d066df1481908f66e684e88b8380 |
completed | June 28, 2026, 7:42 a.m. |
Created at: May 3, 2026, 4:18 p.m.